Rong Chen is an expert in clinical genome informatics with 16 years of experience. He has built clinical genome informatics teams at Mount Sinai and Personalis. He has launched startups and developed NGS products for precision medicine. He has published over 70 papers and invented many patents. He received his Ph.D. from Boston University and has held positions at various academic and industry research laboratories.
MseqDR consortium: a grass-roots effort to establish a global resource aimed ...Human Variome Project
The success of whole exome sequencing (WES) for highly heterogeneous disorders, such as mitochondrial disease, is limited by substantial technical and bioinformatics challenges to correctly identify and prioritize the extensive number of sequence variants present in each patient. The likelihood of success can be greatly improved if a large cohort of patient data is assembled in which sequence variants can be systematically analysed, annotated, and interpreted relative to known phenotype. This effort has engaged and united more than 100 international mitochondrial clinicians, researchers, and bioinformaticians in the Mitochondrial Disease Sequence Data Resource (MSeqDR) consortium that formed in June 2012 to identify and prioritize the specific WES data analysis needs of the global mitochondrial disease community. Through regular web-based meetings, we have familiarized ourselves with existing strengths and gaps facing integration of MSeqDR with public resources, as well as the major practical, technical, and ethical challenges that must be overcome to create a sustainable data resource. We have now moved forward toward our common goal by establishing a central data resource (http://mseqdr.org/) that has both public access and secure web-based features that allow the coherent compilation, organization, annotation, and analysis of WES and mtDNA genome data sets generated in both clinical- and research-based settings of suspected mitochondrial disease patients. The most important aims of the MSeqDR consortium are summarized in the MSeqDR portal within the Consortium overview sections. Consortium participants are organized in 3 working groups that include (1) Technology and Bioinformatics; (2) Phenotyping, databasing, IRB concerns and access; and (3) Mitochondrial DNA specific concerns. The online MSeqDR resource is organized into discrete sections to facilitate data deposition and common reannotation, data visualization, data set mining, and access management. With the support of the United Mitochondrial Disease Foundation (UMDF) and the NINDS/NICHD U54 supported North American Mitochondrial Disease Consortium (NAMDC), the MSeqDR prototype has been built. Current major components include common data upload and reannotation using a novel HBCR based annotation tool that has also been made publicly available through the website, MSeqDR GBrowse that allows ready visualization of all public and MSeqDR specific data including labspecific aggregate data visualization tracks, MSeqDR-LSDB instance of nearly 1250 mitochondrial disease and mitochodnrial localized genes that is based on the Locus Specific Database model, exome data set mining in individuals or families using the GEM.app tool, and Account & Access Management. Within MSeqDR GBrowse it is now possible to explore data derived from MitoMap, HmtDB, ClinVar, UCSC-NumtS, ENCODE, 1000 genomes, and many other resources that bioinformaticians recruited to the project are organizing.
This document provides a summary of Ana Gervassi's qualifications and experience. She has over 20 years of experience in immunology, infectious diseases, vaccine research, and program management. She is currently the Cellular Immunology Subcore Director at the Center for AIDS Research and a Senior Scientist at the Center for Infectious Disease Research, where she manages a research laboratory.
V. Anne Westbrook has over 20 years of experience in public health research, writing, and program management. She has extensive experience in infectious diseases, immunology, vaccine development, and other areas of biomedical research. She has authored 24 peer-reviewed publications and co-authored patents and grant proposals. Westbrook has also managed research programs with budgets up to $5 billion as a program manager. She holds a Ph.D. in Cell Biology and seeks to utilize her expertise in a leadership position.
Homa Assar has over 15 years of experience as a technical writer and editor for the National Cancer Institute and NIH. She has expertise in writing for clinical trials, FDA regulations, and informed consent forms. Her experience also includes maintaining databases, translating medical documents, and authoring scientific publications. She is highly skilled in English, Persian, French, Italian, and German.
This document provides a summary of Mark Ebbert's education and experience. It includes details of his postdoctoral research at BYU developing algorithms for genome assembly and analysis. It also outlines his PhD from BYU focusing on epistasis in Alzheimer's disease genetics. Further experience includes teaching, research roles, and publications in computational biology and bioinformatics.
Romain Banchereau is a computational biologist and translational immunologist focused on analyzing immune cell populations and transcriptional profiles from human disease cohorts. He has expertise in genomics analysis of blood and immune cells from infectious and autoimmune disease patients. Through bioinformatics analysis, he identifies biomarkers for disease diagnosis, prognosis, and response to treatment. He currently works as a research associate applying these skills to study lupus, juvenile arthritis, and complications during pregnancy with SLE.
Rong Chen is an expert in clinical genome informatics with 16 years of experience. He has built clinical genome informatics teams at Mount Sinai and Personalis. He has launched startups and developed NGS products for precision medicine. He has published over 70 papers and invented many patents. He received his Ph.D. from Boston University and has held positions at various academic and industry research laboratories.
MseqDR consortium: a grass-roots effort to establish a global resource aimed ...Human Variome Project
The success of whole exome sequencing (WES) for highly heterogeneous disorders, such as mitochondrial disease, is limited by substantial technical and bioinformatics challenges to correctly identify and prioritize the extensive number of sequence variants present in each patient. The likelihood of success can be greatly improved if a large cohort of patient data is assembled in which sequence variants can be systematically analysed, annotated, and interpreted relative to known phenotype. This effort has engaged and united more than 100 international mitochondrial clinicians, researchers, and bioinformaticians in the Mitochondrial Disease Sequence Data Resource (MSeqDR) consortium that formed in June 2012 to identify and prioritize the specific WES data analysis needs of the global mitochondrial disease community. Through regular web-based meetings, we have familiarized ourselves with existing strengths and gaps facing integration of MSeqDR with public resources, as well as the major practical, technical, and ethical challenges that must be overcome to create a sustainable data resource. We have now moved forward toward our common goal by establishing a central data resource (http://mseqdr.org/) that has both public access and secure web-based features that allow the coherent compilation, organization, annotation, and analysis of WES and mtDNA genome data sets generated in both clinical- and research-based settings of suspected mitochondrial disease patients. The most important aims of the MSeqDR consortium are summarized in the MSeqDR portal within the Consortium overview sections. Consortium participants are organized in 3 working groups that include (1) Technology and Bioinformatics; (2) Phenotyping, databasing, IRB concerns and access; and (3) Mitochondrial DNA specific concerns. The online MSeqDR resource is organized into discrete sections to facilitate data deposition and common reannotation, data visualization, data set mining, and access management. With the support of the United Mitochondrial Disease Foundation (UMDF) and the NINDS/NICHD U54 supported North American Mitochondrial Disease Consortium (NAMDC), the MSeqDR prototype has been built. Current major components include common data upload and reannotation using a novel HBCR based annotation tool that has also been made publicly available through the website, MSeqDR GBrowse that allows ready visualization of all public and MSeqDR specific data including labspecific aggregate data visualization tracks, MSeqDR-LSDB instance of nearly 1250 mitochondrial disease and mitochodnrial localized genes that is based on the Locus Specific Database model, exome data set mining in individuals or families using the GEM.app tool, and Account & Access Management. Within MSeqDR GBrowse it is now possible to explore data derived from MitoMap, HmtDB, ClinVar, UCSC-NumtS, ENCODE, 1000 genomes, and many other resources that bioinformaticians recruited to the project are organizing.
This document provides a summary of Ana Gervassi's qualifications and experience. She has over 20 years of experience in immunology, infectious diseases, vaccine research, and program management. She is currently the Cellular Immunology Subcore Director at the Center for AIDS Research and a Senior Scientist at the Center for Infectious Disease Research, where she manages a research laboratory.
V. Anne Westbrook has over 20 years of experience in public health research, writing, and program management. She has extensive experience in infectious diseases, immunology, vaccine development, and other areas of biomedical research. She has authored 24 peer-reviewed publications and co-authored patents and grant proposals. Westbrook has also managed research programs with budgets up to $5 billion as a program manager. She holds a Ph.D. in Cell Biology and seeks to utilize her expertise in a leadership position.
Homa Assar has over 15 years of experience as a technical writer and editor for the National Cancer Institute and NIH. She has expertise in writing for clinical trials, FDA regulations, and informed consent forms. Her experience also includes maintaining databases, translating medical documents, and authoring scientific publications. She is highly skilled in English, Persian, French, Italian, and German.
This document provides a summary of Mark Ebbert's education and experience. It includes details of his postdoctoral research at BYU developing algorithms for genome assembly and analysis. It also outlines his PhD from BYU focusing on epistasis in Alzheimer's disease genetics. Further experience includes teaching, research roles, and publications in computational biology and bioinformatics.
Romain Banchereau is a computational biologist and translational immunologist focused on analyzing immune cell populations and transcriptional profiles from human disease cohorts. He has expertise in genomics analysis of blood and immune cells from infectious and autoimmune disease patients. Through bioinformatics analysis, he identifies biomarkers for disease diagnosis, prognosis, and response to treatment. He currently works as a research associate applying these skills to study lupus, juvenile arthritis, and complications during pregnancy with SLE.
Jan Peters has over 17 years of experience in research and analytical testing in academia and industry. They have extensive experience leading teams and projects, developing methods and conducting research. Their expertise includes molecular biology, cell biology, biochemistry, and microbiology techniques. They hold a PhD in Biochemistry and Microbiology from Leibniz University Hannover and have worked in various roles at Eurofins Lancaster Laboratories, the Regional Biocontainment Laboratory, and the University of Tennessee Health Science Center.
Ben Goertzel AIs, Superflies and the Path to Immortality - singsum au 2011Adam Ford
This document discusses how AI and advanced AGI can help address challenges in biology, biopharma, and longevity research. It describes OpenBiomind, an open-source machine learning framework for genomic analysis. It also summarizes research analyzing the genetics of long-lived fruit flies using AI, finding key genes and networks related to aging. Finally, it outlines the OpenCog project's work towards advanced, human-level AGI.
Making the most of phenotypes in ontology-based biomedical knowledge discoveryMichel Dumontier
A phenotype is an observable characteristic of an individually and typically pertains to its morphology, function, and behavior. Phenotypes, whether observed at the bench or the bedside, are increasingly being used to gain insight into the diagnosis, mechanism, and treatment of disease. A key aspect of these approaches involve comparing phenotypes that are defined in multiple terminologies that often cater to altogether different organisms, such as mice and humans. In this seminar, I will discuss computational approaches for harmonizing and utilizing phenotypes for translational research. We will examine case studies which involve the computation of semantic similarity including the use of phenotypes to inform clinical diagnosis of rare diseases, to identify human drug targets using mice knock-out models, and to explore phenotype-based approaches for drug repositioning .
Jonathan Vazquez-Perez is seeking a Ph.D. in molecular and cellular biology. He graduated from the University of Texas at El Paso with a B.S. in Microbiology. He has extensive research experience in pathogenic microbiology, virology, and molecular and cellular biology. His skills include molecular cloning, protein analysis, cell culture, and leadership. He has generated several scientific findings and received best poster awards at conferences. His references include past research mentors who can attest to his thorough, hard work and ability to plan tasks and document results.
How Can We Make Genomic Epidemiology a Widespread Reality? - William HsiaoWilliam Hsiao
The document discusses genomic epidemiology and the requirements to bring genomic sequencing into routine public health practice. It outlines two parts: (1) what genomic epidemiology is and why it is important; and (2) the requirements for genomic sequencing to be used routinely in public health. Whole genome sequencing is seen as a way to generate high quality pathogen genomes quickly and allow for more detailed tracking of disease spread compared to traditional methods. However, bringing genomic sequencing into public health practice requires overcoming barriers such as the need for user-friendly analysis platforms, training public health personnel in genomics, and improving information sharing between organizations.
Introducing OWL Ontologies - the use of globally accessible controlled vocabularies in the domain of biology, chemistry, health, and data science. The more that data elements and form fields reference these, the more your application and data will become globally connected and adaptable.
The document discusses shortcomings of traditional statistical analysis of molecular biomarker data and advocates for a biology-driven approach. It proposes building active knowledge repositories focused on specific diseases or areas by extracting relevant molecular entities and pathways from databases, literature mining, and integrating experimental molecular profiling data. The repositories would parameterize biological relationships to form statistical models and generate hypotheses to guide biomarker study design and drive multivariate data analysis in a hypothesis-testing framework.
Forum on Personalized Medicine: Challenges for the next decadeJoaquin Dopazo
Bioinformatics and Big Data in the era of Personalized Medicine
10th Anniversary Instituto Roche Forum on Personalized Medicine: Challenges for the next decade.
Santiago de Compostela (Spain), September 25th 2014
ERIC is a bioinformatics resource center funded by NIAID that focuses on integrating data from five enteropathogens and related organisms. It provides genome assemblies, annotations, comparative genomics tools, and text mining of literature to extract terms and relationships relevant to bacterial pathogenesis. Text mining allows quick summarization of publications and search across extracted data, facilitating faster conclusions than reading individual papers. All of ERIC's data and tools are freely available to the scientific community.
Spanish National Rare Diseases Biobank (BioNER) was created in 2013 to establish a framework for systematically collecting biological samples and clinical data from rare disease patients, families, and controls. BioNER aims to promote research and support diagnosis and treatment development. It operates under open access policies to widely share data and enable collaboration. BioNER follows ethical standards for informed consent and protecting donor privacy. It connects to the Spanish Rare Diseases Patients Registry and is part of broader national and European biobanking networks to facilitate rare disease research through harmonized policies, standardized procedures, and accessible sample catalogues and data.
Sue Suyeon Ryu is seeking a position in research and development. She has a B.S. in Biochemistry/Chemistry from UC San Diego and was a research associate at Takeda Pharmaceuticals from 2013-2015. There, she performed immunohistochemistry, fluorescence, and FACS analysis to evaluate diagnostic antibodies and biomarkers. She also has experience with transmission electron microscopy, image analysis, and histological evaluation from her volunteer work at UCSD.
This document provides a summary of the 2012 Translational Bioinformatics conference. It highlights several important papers presented at the conference in areas like systems medicine, finding and defining phenotypes, biomarkers, and genomic infrastructure. The document outlines the goals of the conference, the process used to select papers, caveats about the selection, and thanks various contributors. It then briefly summarizes several key papers from the conference in these areas.
This document outlines challenges and opportunities in personal genomics and using big data to better define health-related phenotypes. It discusses:
1) Traditional genetic studies of one allele or trait at a time were slow; genome-wide association studies explored many alleles but ill-defined phenotypes reduced precision.
2) Personal genomics via direct-to-consumer testing now sequences whole populations cheaply but phenotype measurement via questionnaires lacks accuracy.
3) Total evidence synthesis combining diverse health data sources could more precisely define population-centric phenotypes to better match with genomic data and enable more meaningful insights. This represents both a challenge and rewarding opportunity.
Asela Dassanayake successfully completed The Data Scientist's Toolbox course offered through Coursera by Johns Hopkins University with distinction in February 2015. The course provided an overview of the conceptual ideas and practical tools used by data analysts and scientists such as version control, markdown, git, GitHub, R, and RStudio. The course was instructed by Jeffrey Leek, Roger Peng, and Brian Caffo of Johns Hopkins Bloomberg School of Public Health.
The document provides an overview of biobanking from the perspective of a user. It discusses three examples of biobanking: 1) Using postmortem brain samples from the NIH NeuroBioBank to validate findings related to Sturge-Weber syndrome. 2) Establishing a biobank for Sturge-Weber syndrome. 3) Discovering mosaic mutations in autism samples by analyzing genomic data and then validating findings using samples from existing biobanks. It also outlines several issues, lessons, and principles for biobanking including usefulness, existing biobanks, importance of identifiers, role of data science, use of standards, informed consent considerations, and ongoing needs and opportunities.
HIV Cure Research presented by Kate Krauss, director of AIDS Policy Project at the Fenway Health Center community education conference: An End To AIDS - How A State Bill Can Change Everything hosted by SearchForACure.org, the Fenway Health Center, and the MA Dept. of Public Health
Bioinformatics emerged as a field in the 1970s-1980s as areas of biology increasingly relied on computational methods. There were two main types of students in bioinformatics - computer scientists interested in biology and biologists skilled in computing. The bioinformatics market continues to grow worldwide and major employers include pharmaceutical and biotech companies. A career in bioinformatics requires strong skills in biology, computing, programming, data analysis, visualization and teamwork. Opportunities exist in areas like sequence assembly, genomic analysis, functional genomics, and database administration.
A machine learning and bioinformatics approach was used to identify non-invasive miRNA biomarkers for early detection of non-small cell lung cancer (NSCLC). 13 miRNAs were found to be consistently underexpressed in NSCLC tissue, blood and serum across 4 datasets. Kaplan-Meier analysis showed 6 miRNAs had prognostic power. A random forest model identified a 3-miRNA panel (miR-320e, miR-103a, miR-526b) that detected NSCLC with 91.5% accuracy. These miRNAs were also prognostic for lung adenocarcinoma survival. An online tool called BiomarkerGenie was created to automate biomarker selection from omics data.
Robert Pesich_PAVA_Stanford Resume v. 8_22_16Robert Pesich
Robert Pesich has extensive experience managing laboratory operations and research projects. He has overseen the daily activities of 25 researchers at Stanford University and the Palo Alto VA, including managing budgets, equipment, and regulatory compliance. Pesich has specialized skills in tissue sample processing, gene expression analysis, and bioinformatics. He has authored several publications characterizing gene expression profiles in normal and diseased tissues. Currently, Pesich also serves as President of a poetry non-profit organization.
This curriculum vitae summarizes the qualifications and experience of Weiliang Qiu. Qiu has over 12 years of experience in data analysis, especially of clinical trial and observational data. He has published over 70 peer-reviewed papers and edited two academic journals. Qiu has a Ph.D. in Statistics and is currently an Associate Biostatistician and Assistant Professor at Brigham and Women's Hospital, where he provides statistical support for clinical trials and develops novel statistical methods.
Jan Peters has over 17 years of experience in research and analytical testing in academia and industry. They have extensive experience leading teams and projects, developing methods and conducting research. Their expertise includes molecular biology, cell biology, biochemistry, and microbiology techniques. They hold a PhD in Biochemistry and Microbiology from Leibniz University Hannover and have worked in various roles at Eurofins Lancaster Laboratories, the Regional Biocontainment Laboratory, and the University of Tennessee Health Science Center.
Ben Goertzel AIs, Superflies and the Path to Immortality - singsum au 2011Adam Ford
This document discusses how AI and advanced AGI can help address challenges in biology, biopharma, and longevity research. It describes OpenBiomind, an open-source machine learning framework for genomic analysis. It also summarizes research analyzing the genetics of long-lived fruit flies using AI, finding key genes and networks related to aging. Finally, it outlines the OpenCog project's work towards advanced, human-level AGI.
Making the most of phenotypes in ontology-based biomedical knowledge discoveryMichel Dumontier
A phenotype is an observable characteristic of an individually and typically pertains to its morphology, function, and behavior. Phenotypes, whether observed at the bench or the bedside, are increasingly being used to gain insight into the diagnosis, mechanism, and treatment of disease. A key aspect of these approaches involve comparing phenotypes that are defined in multiple terminologies that often cater to altogether different organisms, such as mice and humans. In this seminar, I will discuss computational approaches for harmonizing and utilizing phenotypes for translational research. We will examine case studies which involve the computation of semantic similarity including the use of phenotypes to inform clinical diagnosis of rare diseases, to identify human drug targets using mice knock-out models, and to explore phenotype-based approaches for drug repositioning .
Jonathan Vazquez-Perez is seeking a Ph.D. in molecular and cellular biology. He graduated from the University of Texas at El Paso with a B.S. in Microbiology. He has extensive research experience in pathogenic microbiology, virology, and molecular and cellular biology. His skills include molecular cloning, protein analysis, cell culture, and leadership. He has generated several scientific findings and received best poster awards at conferences. His references include past research mentors who can attest to his thorough, hard work and ability to plan tasks and document results.
How Can We Make Genomic Epidemiology a Widespread Reality? - William HsiaoWilliam Hsiao
The document discusses genomic epidemiology and the requirements to bring genomic sequencing into routine public health practice. It outlines two parts: (1) what genomic epidemiology is and why it is important; and (2) the requirements for genomic sequencing to be used routinely in public health. Whole genome sequencing is seen as a way to generate high quality pathogen genomes quickly and allow for more detailed tracking of disease spread compared to traditional methods. However, bringing genomic sequencing into public health practice requires overcoming barriers such as the need for user-friendly analysis platforms, training public health personnel in genomics, and improving information sharing between organizations.
Introducing OWL Ontologies - the use of globally accessible controlled vocabularies in the domain of biology, chemistry, health, and data science. The more that data elements and form fields reference these, the more your application and data will become globally connected and adaptable.
The document discusses shortcomings of traditional statistical analysis of molecular biomarker data and advocates for a biology-driven approach. It proposes building active knowledge repositories focused on specific diseases or areas by extracting relevant molecular entities and pathways from databases, literature mining, and integrating experimental molecular profiling data. The repositories would parameterize biological relationships to form statistical models and generate hypotheses to guide biomarker study design and drive multivariate data analysis in a hypothesis-testing framework.
Forum on Personalized Medicine: Challenges for the next decadeJoaquin Dopazo
Bioinformatics and Big Data in the era of Personalized Medicine
10th Anniversary Instituto Roche Forum on Personalized Medicine: Challenges for the next decade.
Santiago de Compostela (Spain), September 25th 2014
ERIC is a bioinformatics resource center funded by NIAID that focuses on integrating data from five enteropathogens and related organisms. It provides genome assemblies, annotations, comparative genomics tools, and text mining of literature to extract terms and relationships relevant to bacterial pathogenesis. Text mining allows quick summarization of publications and search across extracted data, facilitating faster conclusions than reading individual papers. All of ERIC's data and tools are freely available to the scientific community.
Spanish National Rare Diseases Biobank (BioNER) was created in 2013 to establish a framework for systematically collecting biological samples and clinical data from rare disease patients, families, and controls. BioNER aims to promote research and support diagnosis and treatment development. It operates under open access policies to widely share data and enable collaboration. BioNER follows ethical standards for informed consent and protecting donor privacy. It connects to the Spanish Rare Diseases Patients Registry and is part of broader national and European biobanking networks to facilitate rare disease research through harmonized policies, standardized procedures, and accessible sample catalogues and data.
Sue Suyeon Ryu is seeking a position in research and development. She has a B.S. in Biochemistry/Chemistry from UC San Diego and was a research associate at Takeda Pharmaceuticals from 2013-2015. There, she performed immunohistochemistry, fluorescence, and FACS analysis to evaluate diagnostic antibodies and biomarkers. She also has experience with transmission electron microscopy, image analysis, and histological evaluation from her volunteer work at UCSD.
This document provides a summary of the 2012 Translational Bioinformatics conference. It highlights several important papers presented at the conference in areas like systems medicine, finding and defining phenotypes, biomarkers, and genomic infrastructure. The document outlines the goals of the conference, the process used to select papers, caveats about the selection, and thanks various contributors. It then briefly summarizes several key papers from the conference in these areas.
This document outlines challenges and opportunities in personal genomics and using big data to better define health-related phenotypes. It discusses:
1) Traditional genetic studies of one allele or trait at a time were slow; genome-wide association studies explored many alleles but ill-defined phenotypes reduced precision.
2) Personal genomics via direct-to-consumer testing now sequences whole populations cheaply but phenotype measurement via questionnaires lacks accuracy.
3) Total evidence synthesis combining diverse health data sources could more precisely define population-centric phenotypes to better match with genomic data and enable more meaningful insights. This represents both a challenge and rewarding opportunity.
Asela Dassanayake successfully completed The Data Scientist's Toolbox course offered through Coursera by Johns Hopkins University with distinction in February 2015. The course provided an overview of the conceptual ideas and practical tools used by data analysts and scientists such as version control, markdown, git, GitHub, R, and RStudio. The course was instructed by Jeffrey Leek, Roger Peng, and Brian Caffo of Johns Hopkins Bloomberg School of Public Health.
The document provides an overview of biobanking from the perspective of a user. It discusses three examples of biobanking: 1) Using postmortem brain samples from the NIH NeuroBioBank to validate findings related to Sturge-Weber syndrome. 2) Establishing a biobank for Sturge-Weber syndrome. 3) Discovering mosaic mutations in autism samples by analyzing genomic data and then validating findings using samples from existing biobanks. It also outlines several issues, lessons, and principles for biobanking including usefulness, existing biobanks, importance of identifiers, role of data science, use of standards, informed consent considerations, and ongoing needs and opportunities.
HIV Cure Research presented by Kate Krauss, director of AIDS Policy Project at the Fenway Health Center community education conference: An End To AIDS - How A State Bill Can Change Everything hosted by SearchForACure.org, the Fenway Health Center, and the MA Dept. of Public Health
Bioinformatics emerged as a field in the 1970s-1980s as areas of biology increasingly relied on computational methods. There were two main types of students in bioinformatics - computer scientists interested in biology and biologists skilled in computing. The bioinformatics market continues to grow worldwide and major employers include pharmaceutical and biotech companies. A career in bioinformatics requires strong skills in biology, computing, programming, data analysis, visualization and teamwork. Opportunities exist in areas like sequence assembly, genomic analysis, functional genomics, and database administration.
A machine learning and bioinformatics approach was used to identify non-invasive miRNA biomarkers for early detection of non-small cell lung cancer (NSCLC). 13 miRNAs were found to be consistently underexpressed in NSCLC tissue, blood and serum across 4 datasets. Kaplan-Meier analysis showed 6 miRNAs had prognostic power. A random forest model identified a 3-miRNA panel (miR-320e, miR-103a, miR-526b) that detected NSCLC with 91.5% accuracy. These miRNAs were also prognostic for lung adenocarcinoma survival. An online tool called BiomarkerGenie was created to automate biomarker selection from omics data.
Robert Pesich_PAVA_Stanford Resume v. 8_22_16Robert Pesich
Robert Pesich has extensive experience managing laboratory operations and research projects. He has overseen the daily activities of 25 researchers at Stanford University and the Palo Alto VA, including managing budgets, equipment, and regulatory compliance. Pesich has specialized skills in tissue sample processing, gene expression analysis, and bioinformatics. He has authored several publications characterizing gene expression profiles in normal and diseased tissues. Currently, Pesich also serves as President of a poetry non-profit organization.
This curriculum vitae summarizes the qualifications and experience of Weiliang Qiu. Qiu has over 12 years of experience in data analysis, especially of clinical trial and observational data. He has published over 70 peer-reviewed papers and edited two academic journals. Qiu has a Ph.D. in Statistics and is currently an Associate Biostatistician and Assistant Professor at Brigham and Women's Hospital, where he provides statistical support for clinical trials and develops novel statistical methods.
This document provides an overview of the November 2000 issue of JALA (Journal of Analytical Laboratories Automation). It describes the development of a novel robotic system for the New York Cancer Project biorepository in collaboration with the Medical Automation Research Center. The biorepository receives 50-100 blood samples per day which are processed robotically to extract, quantify, aliquot and store DNA, plasma and RNA to be accessible to investigators. The robotic system aims to provide rapid random access to the hundreds of thousands of DNA samples stored for high-throughput analysis in studies of gene-environment interactions and cancer risk.
CHI’s Thirteenth Annual High-Content Analysis meeting, the premier event showcasing the latest advancements in HCA applications and technologies, returns to San Diego with a new program. Over the years we have observed the technology mature and its adoption spread into many areas of compound screening/evaluation and functional analysis. The High-Content Analysis meeting will focus on the next steps of technology development, including screening of 3D and physiologically relevant complex models, ultra-high resolution and high-throughput imaging, more advanced image analysis and data management, and new assays and applications. The co-located Second Annual Phenotypic Screening meeting will address the advantages of phenotypic screening vs. target-based screening, and focus on assay development, selection of physiologically relevant models and subsequent target identification, as well as case studies of phenotypic screens from leading pharma. Join the original High-Content Analysis event and get access to two tracks featuring a cutting-edge scientific agenda, expanded exhibit hall and technology showcases, and an offering of technology demonstrations and dinner courses.
Shilpy Joshi is a cancer biologist seeking a position in clinical cancer research and drug development. She has over 6 years of postdoctoral experience working with human cancer samples and mouse models. Her research has focused on cancer metabolism and autophagy, including projects elucidating metabolic differences between kidney tumor and normal cells, and studying the effects of mitochondrial dysfunction on tumorigenesis. She has strong skills in molecular biology, cell culture, animal studies, and collaborative multi-institute projects.
The document discusses the intersection of precision medicine, biomarkers, and healthcare policy. It describes how biomarkers and -omics data can be used for precision medicine to improve diagnostic accuracy, deliver targeted therapies, and stratify patient populations. However, clinical validation of biomarkers now requires large datasets and years of studies due to regulatory and payer requirements. This has reduced incentives for diagnostic innovation. The document also discusses challenges around clinical interpretation of complex multi-omic tests, evolving medical training and workflows, and disconnects between patent and reimbursement policies.
Jeffrey J. Wu has extensive experience in immuno-oncology research and business development consulting. He received degrees from Princeton University and Keck Graduate Institute and currently works as a medical center student at City of Hope conducting protocol management and quantitative pathology analysis. His background includes publications, community service, and skills in databases, data analysis, business intelligence, and Microsoft Office.
Data sharing drivers in precision oncology, biomedical research, and healthcare. Accelerating discovery, innovation, providing credit for all stakeholders - patients, researchers, care providers, payers.
Michael Ward has over 15 years of experience in biomedical research and drug development. He currently works as a Senior Clinical Science Specialist at Genentech, where he helps develop clinical trial protocols and analyzes data from Alzheimer's disease studies. Prior to this role, he worked as a Senior Manager leading statistical analysis teams. Dr. Ward has extensive experience across multiple disciplines including neuropsychology, bioinformatics, data management, and clinical research.
Dr. Dennis Wang discusses possible ways to enable ML methods to be more powerful for discovery and to reduce ambiguity within translational medicine, allowing data-informed decision-making to deliver the next generation of diagnostics and therapeutics to patients quicker, at lowered costs, and at scale.
The talk by Dr. Dennis Wang was followed by a panel discussion with Mr. Albert Wang, M. Eng., Head, IT Business Partner, Translational Research & Technologies, Bristol-Myers Squibb.
This document provides a summary of the professional experience and qualifications of Venkatakrishna Shyamala, Ph.D. It outlines her roles as an independent consultant in molecular diagnostics and blood testing since 2008, as well as her previous positions in research and development roles at various biotechnology companies focused on developing diagnostic assays and next generation sequencing technologies for infectious diseases. Her expertise includes assay development, scientific affairs, and securing external funding.
This document provides a summary of the work experience and qualifications of Venkatakrishna Shyamala, Ph.D. It outlines her extensive experience in molecular diagnostics and blood testing spanning over 30 years, including roles leading research and development teams at multiple biotech companies. Her areas of expertise include assay development, scientific affairs, and evaluating nucleic acid testing technologies.
This document provides a summary and review of notable publications in translational bioinformatics from approximately 2014 to early 2015. It begins with an introduction and overview of the goals and process for selecting publications. Several key topics and publications are then highlighted, including precision medicine and clinical prediction models, variation analysis, cancer genomics, clinical applications of genomics, pharmacogenomics, systems biology approaches, and natural language processing. The document concludes with thanks and acknowledges limitations in scope.
Math, Stats and CS in Public Health and Medical ResearchJessica Minnier
Jessica Minnier gave a talk on her career path from studying mathematics at Lewis & Clark College to her current position as an Assistant Professor in biostatistics. She discussed how biostatistics, bioinformatics, and computational biology are applied in medical research, using examples like analyzing RNA sequencing data and building predictive models from electronic health records. Minnier also shared resources for learning more about careers in public health research and statistics.
Katrina Welch-Reardon has extensive scientific research experience and seeks a business role in a scientific organization. She has a Ph.D. in Biological Sciences from UC Irvine and certificates in bioscience management. Her career includes roles managing admissions events, scientific writing and project management, and graduate research investigating angiogenesis. She has strong communication, organizational and leadership skills as shown through successful event planning, publishing papers, and managing teams of researchers.
This document provides a summary of Venkatakrishna Shyamala's background and experience in molecular diagnostics and blood testing spanning over 25 years. It includes information on her educational background, work experience at various biotech companies focusing on assay development and next generation technologies, areas of expertise, selected publications, and extra mural funding. She has consulted for various companies and organizations, and served on committees providing expertise in molecular methods for clinical testing.
5th Tumor Models Boston July 2017 BrochureDiane McKenna
Tumor Models Boston 2017 will address the preclinical & clinical developments of the most promising therapies including targeted therapies, check-point inhibitors & CAR-T therapies and how these findings can be utilized to bridge the gap between preclinical and clinical studies.
Matthew W. McNatt has extensive experience in biomedical research and leadership. He co-founded Celleritas Bioscience where he served as Chief Science Officer and helped secure intellectual property protection. As a postdoctoral fellow, he designed bispecific antibodies and collaborated on elucidating protein structures. He has authored seven research papers and mentored students. McNatt has strong expertise in molecular biology, biochemistry, virology, and microscopy techniques. He holds a PhD from the University of Colorado and seeks new opportunities in science leadership.
Join us in Boston this coming Fall to attend Cambridge Healthtech Institute's (CHI) 2nd Annual FAST: Functional Analysis & Screening Technologies Congress on November 17-19, 2014 and meet with a community of 250+ biologists, screening managers, assay developers, engineers and pharmacologists dedicated to improving in vitro cell models and phenotypic screening to advance drug discovery and development at 6 conferences: Phenotypic Drug Discovery (Part I & II), Engineering Functional 3D Models, Screening and Functional Analysis of 3D Models, Organotypic Culture Models for Toxicology and Physiologically-Relevant Cellular Tumor Models for Drug Discovery. Delegates have the opportunity to share insights in interactive panel discussions and connect during networking breaks. View innovative technologies and scientific research revolutionizing early-stage drug discovery in the exhibit/poster hall.
Bryan Soper has extensive experience in pharmaceutical competitive intelligence, medical writing, and data analysis. He currently performs contract work analyzing clinical trials and assessing drug approval likelihoods for Genentech. Previously he has analyzed cancer models and clinical trials to identify correlations. He holds a PhD in Molecular Biology from Cornell University and has worked as a postdoctoral scholar at UCSF investigating drug targets.
Success is often not achievable without facing and overcoming obstacles along the way. To reach our goals and achieve success, it is important to understand and resolve the obstacles that come in our way.
In this article, we will discuss the various obstacles that hinder success, strategies to overcome them, and examples of individuals who have successfully surmounted their obstacles.
In the intricate tapestry of life, connections serve as the vibrant threads that weave together opportunities, experiences, and growth. Whether in personal or professional spheres, the ability to forge meaningful connections opens doors to a multitude of possibilities, propelling individuals toward success and fulfillment.
Eirini is an HR professional with strong passion for technology and semiconductors industry in particular. She started her career as a software recruiter in 2012, and developed an interest for business development, talent enablement and innovation which later got her setting up the concept of Software Community Management in ASML, and to Developer Relations today. She holds a bachelor degree in Lifelong Learning and an MBA specialised in Strategic Human Resources Management. She is a world citizen, having grown up in Greece, she studied and kickstarted her career in The Netherlands and can currently be found in Santa Clara, CA.
Learnings from Successful Jobs SearchersBruce Bennett
Are you interested to know what actions help in a job search? This webinar is the summary of several individuals who discussed their job search journey for others to follow. You will learn there are common actions that helped them succeed in their quest for gainful employment.
We recently hosted the much-anticipated Community Skill Builders Workshop during our June online meeting. This event was a culmination of six months of listening to your feedback and crafting solutions to better support your PMI journey. Here’s a look back at what happened and the exciting developments that emerged from our collaborative efforts.
A Gathering of Minds
We were thrilled to see a diverse group of attendees, including local certified PMI trainers and both new and experienced members eager to contribute their perspectives. The workshop was structured into three dynamic discussion sessions, each led by our dedicated membership advocates.
Key Takeaways and Future Directions
The insights and feedback gathered from these discussions were invaluable. Here are some of the key takeaways and the steps we are taking to address them:
• Enhanced Resource Accessibility: We are working on a new, user-friendly resource page that will make it easier for members to access training materials and real-world application guides.
• Structured Mentorship Program: Plans are underway to launch a mentorship program that will connect members with experienced professionals for guidance and support.
• Increased Networking Opportunities: Expect to see more frequent and varied networking events, both virtual and in-person, to help you build connections and foster a sense of community.
Moving Forward
We are committed to turning your feedback into actionable solutions that enhance your PMI journey. This workshop was just the beginning. By actively participating and sharing your experiences, you have helped shape the future of our Chapter’s offerings.
Thank you to everyone who attended and contributed to the success of the Community Skill Builders Workshop. Your engagement and enthusiasm are what make our Chapter strong and vibrant. Stay tuned for updates on the new initiatives and opportunities to get involved. Together, we are building a community that supports and empowers each other on our PMI journeys.
Stay connected, stay engaged, and let’s continue to grow together!
About PMI Silver Spring Chapter
We are a branch of the Project Management Institute. We offer a platform for project management professionals in Silver Spring, MD, and the DC/Baltimore metro area. Monthly meetings facilitate networking, knowledge sharing, and professional development. For more, visit pmissc.org.
Joyce M Sullivan, Founder & CEO of SocMediaFin, Inc. shares her "Five Questions - The Story of You", "Reflections - What Matters to You?" and "The Three Circle Exercise" to guide those evaluating what their next move may be in their careers.
A Guide to a Winning Interview June 2024Bruce Bennett
This webinar is an in-depth review of the interview process. Preparation is a key element to acing an interview. Learn the best approaches from the initial phone screen to the face-to-face meeting with the hiring manager. You will hear great answers to several standard questions, including the dreaded “Tell Me About Yourself”.
1. Rong Chen, Ph.D. 1
CURRICULUM VITAE
RONG CHEN
Work Address:
Assistant Professor, Director of Clinical Genome Informatics
Department of genetics and Genomic Sciences
Icahn School of Medicine at Mount Sinai
1255 5th
Avenue, New York, NY
Telephone: (858)837-2265 Email: rongch60@gmail.com
Homepage: http://rongchenlab.org/
Google Citations: http://tinyurl.com/3lps7cb (citations 6136; h-index 36)
Summary:
A recognized expert with 15 years of experience on translational bioinformatics and genomics,
specialized on developing databases, genome repositories, pipeline, clinical application, and
commercial products to analyze next generation sequencing data, and interpret personal genomes
for clinical diagnosis, protective alleles, precision medicine, and predictive disease risk.
Highlights:
• Built clinical genome informatics teams from scratch at Mount Sinai and Personalis
• Science team to launch a startup company LifeMap Solutions for mobile health
• Launched a startup company Personalis and won the VA's contract for the Million Veteran
Genome project
• Scientific advisor for various next generation sequencing companies, including Bina
Technologies and Tute Genomics
• Developed NGS products for the precision medicine of cancer, clinical diagnosis of rare
diseases, and disease risk assessment of healthy individuals
• Supervises genome, exome, RNA-Seq, and Panel sequencing and analysis including clinical,
research, and production sequencing at Mount Sinai
• Published over 70 papers in top tier journals, including Lancet, Cell, Nature Biotechnology,
Nature Methods, Science Translational Research, American J Human Genetics, PLoS Genetics,
PLoS Computational Biology, Genomic Research, Genome Biology, PNAS, American J
Transplant, J Clinical Investigation
• Invented many patents, software, and databases on translational medicine
Education:
1999-2003 Boston University, Boston, MA, USA
Ph.D., M.S. in Bioinformatics
1994-1997 Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai
M.S. in Structural Biology
1989-1994 University of Science and Technology of China, Hefei, Anhui, China
B.S. in Chemical Physics
Work Experience:
Icahn School of Medicine at Mount Sinai, New York, NY 06/13-Present
Directors of Clinical Genome Informatics, Assistant Professor, Dept. of Genetics and Genomic
Sciences
• Build and lead a clinical genome informatics team with over 10 bioinformatics scientists and
software engineers
• Build databases, genome repositories, and clinical applications to interpret personal genome for
precision medicine, clinical diagnosis, protective alleles, and disease mechanism
2. Rong Chen, Ph.D. 2
• Lead personalized cancer therapy project, build a pipeline to sequence, analyze, and interpret
tumor samples and create clinical reports to recommend personalized therapeutics and clinical
trials for patients with colon cancer, breast cancer, and other tumor types
• Identify protective alleles as therapeutics for Alzheimer’s disease, cardiovascular diseases
• Identify driver landscape of parathyroid carcinoma
• Lead the resilience project, build Mendelian disease mutation panel, search 600,000 genomes,
and identify 13 unexpected heroes who are resilient to childhood diseases
• Build a reference variant store with 470 million genetic variants with observed frequencies in a
wide variety of disease and healthy states using Hadoop-based infrastructure
• Mine 30 million abstracts and 3 million full text and build VarImpact database with
comprehensive phenotypic impact of genetic variants at gene, protein, pathway, cellular, and
organism levels
• Build disease networks through integrating genetic, EMR, and literature
• Build NGS panels and evaluate the performance between HiSeq and Proton
• Catalog and identify breast cancer risk variants through large scale sequencing
• Develop chrGeneticist to enable clinical geneticists to distribute, annotate, review, and assign
pathogenicity to genetic variants in clinical sequencing
Personalis, Menlo Park, CA 12/11-05/13
Directors of Predictive Medicine
• Built a team of Bioinformatics Scientist, Software Engineer, Database Developer, and Statistical
Geneticist to interpret human genomes for rare variant discovery, disease risk assessment, and
clinical diagnosis on personal genome, family-based studies, and large case/control studies
• Designed and developed several NGS products, including genome annotation, rare variant
discovery, and personal genome report
• Built a comprehensive disease-variant database from 20,000 human genetic papers through
manual curation
Stanford University, Stanford, CA 11/05-02/06, 03/07-11/11
Bioinformatics Scientist, Butte Lab
• Built comprehensive data warehouse on genetics, genomics, epidemiology, evolutionary, and
clinics, which enabled many startups, diagnostic biomarkers, novel therapeutics, and patents
from Butte Lab
• Led a large curation team to build a comprehensive disease-variant database Varimed from
literature
• Built a pipeline to interpret human genome and predict personal risk on hundreds of diseases
• Built AILUN to extract, annotate, and analyze millions of gene expression data across thousands
of platforms in GEO, and identified and validated many diagnostic biomarkers
• Identified and validated several protein biomarkers for the diagnosis of cross-organ transplant
rejection
• Developed several tools to integrate various types of molecular measurements to drive the
discovery of diagnostic biomarkers and therapeutic targets
Quest Diagnostics Nichols Institute, San Juan Capistrano, CA 03/06-02/07
Principal Software Engineer
• Supervised two bioinformatics programmers
• Developed diagnostic assays on Cancer of Unknown Primary Origin, Thyroid Carcinoma,
Prostate Carcinoma, and Liver Fibrosis
3. Rong Chen, Ph.D. 3
• Developed a web portal to assess the clinical significance of DNA mutations by integrating
sequence, structure, alternative splicing, and evolutionary data
Abgenix (bought by Amgen), Fremont, CA 07/04-11/05
Senior Computational Biologist
• Developed a pipeline to build high-quality atomic structure of antibodies from sequences to
support therapeutic antibody discovery on oncology
• Classified the CDR regions of thousands of antibodies into novel canonical structures
Accelrys (became BIOVIA), San Diego, CA 08/03-06/04
Senior Computational Biologist
• Development of a high-throughput genomic structure prediction and functional annotation
software GeneAtlas in DS Modeling
Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, China 08/97-08/98
Research Associate
• Protein chemistry and crystallography analysis on two ribosome-inactivating proteins
Honors and Professional Services:
• Scientific Advisor and founding member, LifeMap Solutions (http://www.lifemap-
solutions.com/ ), New York, NY, 2014-Present,
• Scientific Advisor, Bina Technologies (http://www.binatechnologies.com/) , Redwood City,
CA, 2014-Present
• Scientific Advisor, Tute Genomics (http://www.tutegenomics.com/) , Provo, UT, 2013-Present
• ICHG Young Investigator Awards, International Congress of Human Genetics, 2011
• Works reported by MIT Technology Review, BBC News, and Business Week, GenomeWeb
News, NPR radio, Wall Street Journal, Market Watch
• A paper on “Clinical assessment incorporating personal genome sequence” has been identified
by Thomson Reuters Essential Science IndicatorsSM
as a featured New Hot Paper in the field of
Clinical Medicine
• Interviewed by Science, Genome Technology, GenomeWeb, ebiotrade
• Reviewer for Proteins, BMC Bioinformatics, J. of Structural Biolog, Evolutionary
Bioinformatics, Biology Direct, Pacific Symposium on Biocomputing, and RECOMB, J.
translational Medicine, J of Biomedical Informatics, PLoS One, Database, ISMB, AMIA TBI,
New England Journal of Medicine
• Committee for The Life Science Computational Systems Bioinformatics Conference
• Committee for Biomedical Computation at Stanford Symposium
Peer Reviewed Research Papers:
1. Ayers K.A., Reva B., Chen R., Assessment of cancer mutational burden from the 1000
genomes sequencing data (in preparation)
2. Hakenberg J., Cheng W., Thomas P., Chen R., A global repository for genetic variants allows
platform-independent integration of annotation (under review)
3. Glicksberg B., Li L., Badgeley M.A., Kosoy R., Hakenberg J., Beckmann N.D., Hoffman G.E.,
Ruderfer D.M., Ayers K.L., Ma M., Shameer K., Schadt E.E., Loos R.J., Pho N., Patel C.J.,
Chen R.*, Dudley J.T.*, Integrative analysis of demographic factors underlying disease
comorbidity networks (under review) (* co-corresponding authors)
4. Chen R., Shi L., Hakenberg J., Brian N., Sklar P., Zhang J., Zhou H., Tian L., Prakash O.,
Lemire M., Sleiman P., Cheng W., Chen W., Shah H., Shen Y., Fromer M., Omberg L.,
Deardorff M.A., Zackai E., Bobe J.R., Levin E., Hudson T., Groop L., Wang J., Hakonarson H.,
4. Rong Chen, Ph.D. 4
Wojcicki A., Diaz G.A., Edelmann L., Schadt E.E., Friend S., A systematic retrospective search
of 589,306 genomes for individuals resilient to severe childhood diseases (under review)
5. Li L., Cheng W., Glicksberg B.S., Gottesman O., Tamler R., Chen R., Bottinger E.P., Dudley
J.T., Identification of type 2 diabetes patient subtypes and molecular markers through
topological analysis of patient similarity networks (under review)
6. Cheng W., Hakenberg J., Li S., Chen R., DIVAS: a centralized genetic variant repository
representing 150,000 individuals from multiple disease cohorts Bioinformatics (in press)
7. Wang J., Liao J., Zhang J., Cheng W., Hakenberg J., Ma M., Webb B.D., Ramasamudram-
chakravarthi R., Karger L., Mehta L., Kornreich R., Diaz G.A., Li S., Edelmann L., Chen R.,
ClinLabGeneticist: A tool for clinical management of genetic variants from whole exome
sequencing in clinical genetic laboratories Genome Med 2015 7:7
8. Luo W., Obeidat M., Di Narzo A.F., Chen R., Sin D.D., Pare P.D., Hao K. Airway epithelial
expression quantitative trait loci reveal genes underlying asthma and other airway diseases Am J
Respir Cell Mol Biol. 2015 Jun 23.
9. Hao K., Di Narzo A.F., Ho L., Luo W., Li S., Chen R., Li T., Dubner L., Pasinetti G.M., Shared
genetic etiology underlying Alzheimer’s Disease and type 2 diabetes Mol Aspects Med. 2015
June 23. Pii:S0098-2997(15)00041-2. Doi: 10.1016/j.mam.2015.06.006.
10. Ma M., Ru Y., Chuang L., Hsu N., Shi L., Hakenberg J., Cheng W., Uzilov A., Ding W., Chen
R., Disease-associated variants in different categories of disease locating in distinct regulatory
elements BMC Genomics 2015;16(Suppl 8):S3
11. Glicksberg B.S., Li L., Cheng W., Shameer K., Hakenberg J., Castellanos R., Meng M., Shi L.,
Shah H., Dudley J.T., Chen R., an integrated pipeline for multi-modal discovery of disease
relationships Pac Symp Biocomputp 2015:407-18
12. Menon M.C., Chuang P.Y., Li Z., Wei C., Zhang W., Luan Y., Yi Z., Xiong H., Woytovich C.,
Greene I., Overbey J., Rosales I., Bagiella E., Chen R., Ma M., Li L., Ding W., Djamali A.,
Saminego M., O'Connell P.J., Gallon L., Colvin R., Schroppel B., He J.C., Murphy B. Intronic
locus determines SHROOM3 expression and potentiates renal allograft fibrosis. J Clin Invest.
2014 Dec 1.
13. Enns G.M., Shashi V., Bainbridge M., Gambello M.J., Zahir F.R., Bast T., Crimian R., Schoch
K., Platt J., Cox R., Bernstein J.A., Scavina M., Walter R.S., Bibb A., Jones M., Hegde M.,
Graham B.H., Need A.C., Oviedo A., Schaaf C.P., Boyle S., Butte A.J., Chen R., Clark M.J.,
Haraksingh R., Cowan T.M., He P., Langlois S., Zoghbi H.Y., Snyder M., Gibbs R.A., Freeze
H.H., Goldstein D.B. Mutations in NGLY1 cause an inherited disorder of the endoplasmic
reticulum-associated degradation pathway. Genet Med. 2014 Mar 20. doi:
10.1038/gim.2014.22.
14. SEQC/MAQC-III Consortium. A comprehensive assessment of RNA-seq accuracy,
reproducibility and information content by the Sequencing Quality Control Consortium. Nat
Biotechnol. 2014 Sep;32(9):903-14. doi: 10.1038/nbt.2957.
15. Li L., Ruau D.J., Patel C.J., Weber S.C., Chen R., Tatonetti N.P., Dudley J.T., Butte A.J.,
Disease risk factors identified through shared genetic architecture and electronic medical
records. Science translational medicine 2014 Apr 30; 6(234):234ra57-234ra57
16. Patel C.J., Sivadas A., Tabassum R., Preeprem T., Zhao J., Arafat D., Chen R., Morgan A.A.,
Martin G.S., Brigham K.L., Butte A.J., Gibson G. Whole genome sequencing in support of
wellness and health maintenance. Genome Med 2013 Jun27; 5(6):58.
17. Hsu I., Chen R., Ramesh A., Corona E., Kang H.P., Ruau D., Butte A.J. Systematic
identification of DNA variants associated with ultraviolet radiation using a novel Geographic-
Wide Association Study (GeoWAS). BMC Med Genet. 2013 Jun 20;14(1):62.
18. Corona E., Chen R., Sikora M., Morgan A.A., Patel C.J., Ramesh A., Bustamante C.D., Butte
A.J. Analysis of the genetic basis of disease in the context of worldwide human relationships
and migration. PLoS Genet. 2013 May;9(5):e1003447
19. Karczewski K.J., Dudley J.T., Kukurba K.R., Chen R., Butte A.J., Montgomery S.B., Snyder
5. Rong Chen, Ph.D. 5
M. Systematic functional regulatory assessment of disease-associated variants. Proc Natl Acad
Sci U S A 2013 May 20
20. Sigdel T.K., Shoemaker L.D., Chen R., Li L., Butte A.J. Immune response profiling identified
autoantibodies specific to Moyamoya patients. Orphanet J Rare Dis. 2013 Mar 21;8:45.
21. Patel C.J., Chen R., Kodama K., Ioannidis J.P., Butte A.J. Systematic identification of
interaction effects between genome- and environment-wide associations in type 2 diabetes
mellitus. Hum Genet. 2013 May;132(5):495-508.
22. Li L., Ruau D., Chen R., Weber S., Butte A.J. Systematic identification of risk factors for
Alzheimer’s disease through shared genetic architecture and electronic medical records. Pac
Symp Biocomput. 2013:224-35.
23. Li L., Khatri P., Sigdel T.K., Tran T., Ying L., Vitalone M.J., Chen A., Hsieh S., Dai H., Zhang
M., Naesens M., Zarkhin V., Sansanwal P., Chen R., Mindrinos M., Xiao W., Benfield M.,
Ettenger R.B., Dharnidharka V., Mathias R., Portale A., McDonald R., Harmon W., Kershaw
D., Vehaskari V.M., Kamil E., Baluarte H.J., Warady B., Davis R., Butte A.J., Salvatierra O.,
Sarwal M.M. A peripheral blood diagnostic test for acute rejection in renal transplantation. Am
J Transplant. 2012 Oct;12(10):2710-8.
24. Kidd J.M., Gravel S., Byrnes J., Moreno-Estrada A., Musharoff S., Bryc K., Degenhardt J.D.,
Brisbin A., Sheth V., Chen R., McLaughlin S.F., Peckham H.E., Omberg L., Chung C.A.B.,
Stanley S., Pearlstein K., Levandowsky E., Acevedo-Acevedo S., Auton A., Keinan A., Acuña-
Alonzo V., Barquera-Lozano R., Canizales-Quinteros S., Eng C., Burchard E.G., Russell A.,
Reynolds A., Clark A.G., Reese M.G., Lincoln S.E., Butte A.J., Vega FMDL, Bustamante C.D..
Population genetic inference from personal genome data: impact of ancestry and admixture on
human genomic variation. Am J Hum Genet. 2012 Oct 5;91(4):660-71.
25. Gupta R., Ratan A., Rajesh C., Chen R., Kim H.L., Burhans R., Miller W., Santhosh S.,
Davuluri R.V., Butte A.J., Schuster S.C., Seshagiri S., Thomas G. Sequencing and analysis of a
South Asian-Indian personal genome. BMC Genomics. 2012 Aug 31;13:440.
26. Morgan A.A., Chen R., Butte A.J. Clinical utility of sequence-based genotype compared with
that derivable from genotyping arrays. J Am Med Inform Assoc. 2012 Jun;19(e1):e21-e27.
27. Patel C.J., Chen R., Butte A.J. Data-driven integration of epidemiological and toxicological
data to select candidate interacting genes and environmental factors in association with disease.
Bioinformatics. 2012 Jun 15;28(12):i121-6.
28. Ruau D, Dudley, JT, Chen R, Phillips NG, Swan GE, Lazzeroni LC, Clark JD, Butte AJ, Angst
MS. Integrative approach to pain genetics identifies pain sensitivity loci across diseases. PLoS
Comput Biol. 2012;8(6):e1002538.
29. Dudley JT, Kim Y, Liu L, Markov GJ, Gerold K, Chen R, Butte AJ, Kumar S. Human genomic
disease variants: A neutral evolutionary explanation. Genome Res. 2012 Aug;22(8):1383-94.
30. Kang HP, Yang X, Chen R, Zhang B, Corona E, Schadt EE, Butte AJ. Integration of disease-
specific single nucleotide polymorphisms, expression quantitative trait loci and coexpression
networks reveal novel candidate genes for type 2 diabetes. Diabetologia. 2012 Aug;55(8):2205-
13.
31. Keiichi K, Horikoshi M, Toda K, Yamada S, Irie J, Sirota M, Morgan AA, Chen R, Ohtsu H,
Hara K, Maeda S, Kadowaki T, Butte AJ. Expression-based genome-wide association study
links CD44 in adipose tissue with type 2 diabetes. Proc Natl Acad Sci U S A. 2012 May
1;109(18):7049-54.
32. Chen R, Corona E, Sikora M, Dudley JT, Morgan AA, Moreno-Estrada A, Nilsen GB, Ruau D,
Lincoln SE, Bustamante CD, Butte AJ. Type 2 diabetes risk alleles show extreme directional
differentiation among human populations, compared to other diseases. PLoS Genet.
2012;8(4):e1002621.
33. Li L, Wozniak LJ, Rodder S, Heish S, Talisetti A, Wang Q, Esquivel C, Cox K, Chen R,
McDiarmid SV, Sarwal MM. A common peripheral blood gene set for diagnosis of operational
tolerance in pediatric and adult liver transplantation. Am J Transplant. 2012 May;12(5):1218-
6. Rong Chen, Ph.D. 6
28.
34. Dudley J, Chen R, Sanderford M, Butte AJ, Kumar S. Evolutionary meta-analysis of
association studies reveals ancient constraints affecting disease marker discovery. Mol Biol
Evol 2012 Sep;29(9)2087-94.
35. Chen R, Mias GI, Li-Pook-Than J, Jiang L, Lam HYK, Chen R, Miriami E, Karczewski KJ,
Hariharan M, Dewey FE, Habegger L, Clark MJ, Balasubramanian S, Cheng Y, O’Huallachain
M, Dudley JT, Hillenmeyer S, Haraksingh R, Sharon D, Euskirchen G, Lacroute P, Bettinger K,
Im H, Boyle AP, Kasowski M, Grubert F, Seki S, Garcia M, Whirl-Carrillo M, Gallardo M,
Blasco MA, Greenberg PL, Snyder P, Klein TE, Altman RB, Butte AJ, Ashley EA, Nadeau KC,
Gerstein M, Tang H, Snyder M. Personal omics profiling reveals dynamic molecular and
medical phenotypes. Cell. 2012 Mar 16;148(6):1293-307. (Responsible for the methods and
analysis on risk prediction on all complex diseases)
36. Rothbard JB, Kurnellas MP, Adams CM, Su L, Chen R, Fathman CG, Robinson WH, Steinman
L. Therapeutic effects of systemic administration of the chaperone alpha B crystallin associated
with binding proinflammatory plasma proteins. J Biol Chem 2012 Mar 23;287(3):9708-21.
37. Chen R, Dudley JT, Ruau D, Butte AJ. Quantifying multi-ethnic representation in genetic
studies of high mortality diseases. AMIA Summits Transl Sci Proc. 2012;2012:11-8.
38. Lam H.Y.K., Clark M.J., Chen R., Chen R., Natsoulis G., O’Huallachain M., Dewey F.,
Habegger L., Ashley E., Gerstein M.B., Butte A.J., Ji H., Snyder M. (2011) Comparison of two
genome sequencing platforms Nature Biotechnology doi:10.1038
39. Pan S., Dewey F., Perez M., Knowles J., Chen R., Butte A.J., Ashley E. (2011) Personalized
medicine and cardiovascular disease: from genome to bedside Current Cardiovascular Risk
Reports doi:10.1007
40. Engreitz J.M., Chen R., Morgan A.A., Dudley J.T., Mallelwar R., Butte A.J. (2011)
ProfileChaser: searching microarray repositories based on genome-wide patterns of differential
expression Bioinformatics 27: doi:10.1093
41. Clark M.J., Chen R., Lam H., Karczewski K.J., Chen R., Euskirchen G., Butte A.J., Snyder M.
(2011) Performance comparison of Exome DNA sequencing technologies Nature
Biotechnology 29:dio:10.1038
42. Dewey F.E., Chen R., Cordero S.P., Ormond K.E., Caleshu C., Karczewski K.J., Carrillo
M.W., Wheeler M.T., Dudley J.T., Bynes J.K., Cornejo O.E., Knowles J.W., Woon M.,
Sangkuhl K., Gong L., Thorn C.F., Hebert J.M., Capriotti E., David S.P., Pavlovic A., West
A.,West J.S., Thakuria J.V., Ball M.P., Zaranek A.W., Rehm H.L., Church G.M., Bustamante
C.D., Snyder M.P., Altman R.B., Klein T.E., Butte A.J., Ashley E.A. (2011) Phased whole
genome genetic risk in a family quartet using a major allele reference sequence PLoS Genetics
7:e1002280
43. Naesens M., Khatri P., Li L., Sigdel T., Chen R., Vitalone M., Butte A.J., Salvatierra O., Sarwal
M.M. (2011) Progressive histological damage in renal allografts is associated with expression of
innate and adaptive immunity genes Kidney International 80:doi:10.1038/ki2011.245
44. Chen R., Butte A.J. (2011) The reference human genome demonstrates high risk of type 1
diabetes and other disorders Pac Symp Biocomputp 2011:231-42
45. Dudley J.T., Chen R., Butte A.J. (2011) Matching cancer genomes to established cell lines for
personalized oncology Pac Symp Biocomputp 2011:243-52
46. Engereitz J.M., Morgan A.A., Dudley J.T., Chen R., Thathoo R., Altman R.B., Butte A.J.
(2010) Content-based microarray search using differential expression profiles BMC Bioinfo
11:603
47. Chen R., Davydov E.V., Sirota M., Butte A.J. (2010) Non-synonymous and synonymous
coding SNPs show similar likelihood and effect size of human disease association PLoS One
5:e13574
48. Chen R., Sigdel T.K., Li L., Kambham N., Dudley J.T., Heish S.C., Klassen R.B., Chen A.,
Caohuu T., Morgan A.A., Valantine H.A., Khush K.K., Sarwal M.M., Butte A.J. (2010)
7. Rong Chen, Ph.D. 7
Differentially expressed RNA from public microarray data identifies serum biomarkers for
cross-organ transplant rejection and other conditions PLoS Computational. Biology 6:
e1000940
49. Morgan A.A., Chen R., Butte A.J., Ashley E.A. (2010) Clinical assessment incorporating a
personal genome – Authors’ reply Lancet 376:869-70
50. Dudley J.T., Pouliot Y., Chen R., Morgan A.A., Butte A.J. (2010) Translational Bioinformatics
in the cloud: an affordable alternative Genome Medicine 2:51
51. Shi L., Campbell G., Jones W.D., Campagne F., Wen Z., Walker S.J., Su Z., Chu T.,. . Chen R.,
...Puri R.K., Scherf U., Tong W., Wolfinger R.D. (2010) The MAQC-II Project: A
comprehensive study of common practices for the development and validation of microarray-
based predictive models Nature Biotechnology 28:827-38
52. Morgan A.A., Chen R., Butte A. J. (2010) Likelihood Ratios for Genome Medicine Genome
Medicine 2:30
53. Ashley EA, Butte AJ, Wheeler MT, Chen R., Klein TE, Dewey FE, Dudley JT, Ormond KE,
Pavlovic A, Hudgins L, Gong L, Hodges LM, Berlin DS, Thorn CF, Sangkuhl K, Hebert JM,
Woon M, Sagreiya H, Whaley R, Morgan AA, Pushkarev D, Neff NF, Knowles JW, Chou M,
Thakuria J, Rosenbaum A, Zaranek AW, Church G, Greely HT, Quake SR, Altman RB (2010)
Clinical assessment incorporating a personal genome Lancet 375:1525-35
54. Suthram S., Dudley J.T., Chaing A.P., Chen R., Hastie T.J., Butte A.J. (2010) Network-based
elucidation of human disease similarity reveals common functional modules enriched for
pluripotent drug targets PLoS Computational Biology. 6:e1000662
55. Li L., Chen A., Chaudhuri A., Kambham N., Sigdel T., Chen R., Sarwal M. (2010) Compartmental
Localization and Clinical Relevance of MICA Antibodies after Renal Transplantation Transplantation
89: 312-9
56. Cai J.J., Borenstein E., Chen R., Petrov D.A (2009) Similarly strong purifying selection acts on
human disease genes of all evolutionary ages Genome Biology & Evolution 2009:131-144
57. Becker L., Salameh W., Sferruzza A., Zhang K., Chen R., Malik R., Reitz R., Nasser I. Afdhal N.H.
(2009) Validation of Hepascore, compared to simple indices of fibrosis, in US patients with
chronic hepatitis C virus infection. Clinical Gastroenterology and Hepatology 7: 696-701
58. Li L., Wadia P., Chen R., Kambham N, Naesens M., Sigdel T., Miklos D., Sarwal M., Butte A.J. (2009)
Identifying Compartment-specific Alloimmune Targets After Renal Transplantation by Integrating
Transcriptome and Antibodyome Measures. PNAS 106:4148-53
59. Shah N.H., Jonquet C., Chiang A.P., Butte A.J., Chen R., Musen M.A. (2009) Ontology-driven
Indexing of Public Datasets for Translational Bioinformatics
BMC Bioinformatics 10 (supple 2): S1
60. Chen R., Mallelwar R., Thosar A., Venkatasubrahmanyam S., Butte A.J. (2008) GeneChaser:
identifying all biological and clinical conditions in which genes of interest are differentially expressed.
BMC Bioinformatics 9: 548
61. Chen R., Morgan A., Dudley J., Deshpande T., Li L., Kodma K., Chiang A., Butte A.J. (2008) FitSNPs:
Highly Differentially Expressed Genes are More Likely to Have Variants Associated With Disease.
Genome Biology 9: R170
62. Shah N., Chiang A., Butte A.J., Chen R., Musen M., Ontology-driven Indexing of Public Datasets for
Translational Bioinformatics (2008) AMIA Symposium on Translational Bioinformatics
63. Li L., Ying LH., Naesens M., Xiao W., Hsieh S., Sigdel T., Martin J., Chen R., Liu K., Sarwal M.
(2008) Interference of globin genes with biomarker discovery for allograft rejection in peripheral blood
samples. Physiological Genomics 32: 190-197
64. Chen R., Li L, Butte A.J. (2007), AILUN: Reannotating Gene Expression Data Automatically. Nature
Methods 4: 879
65. Lin Y., Chiang A., Yao P., Chen R., Butte A., Lin R., Methodology for Exacting Functional
Pharmacogenomic Experiments from International Repository (2007) AMIA Annual Symp Proc
2007:463-467
66. Mintseris J., Pierce B., Wiehe K., Anderson R., Chen R., Weng Z., (2007) Integrating statistical pair
potentials into protein complex prediction. Proteins 69:511-520
8. Rong Chen, Ph.D. 8
67. Butte A.J., Chen R., (2006) Finding Disease-Related Genomic Experiments Within an International
Repository: First Steps in Translational Bioinformatics, AMIA Annu Symp Proc. 2006:106-110
68. Wiehe K., Pierce B., Mintseris J., Tong W., Anderson R., Chen R., Weng Z. (2005) ZDOCK and
RDOCK Performance in CAPRI Rounds 3, 4, and 5. Proteins 60: 207-213
69. Mintseris J., Wiehe K., Pierce B., Anderson R., Chen R., Janin J., Weng Z. (2005) Protein-Protein
Docking Benchmark 2.0: an Update. Proteins 60: 214-216
70. Li L., Chen R. (joint first authors), Weng Z. (2003) RDOCK: Refinement of Rigid-body Protein
Docking Predictions. Proteins 53: 693-707
71. Chen R., Li L., Weng Z. (2003) ZDOCK: An Initial-stage Protein-Docking Algorithm. Proteins, 52:80-
87
72. Chen R., Tong W., Mintseris J., Li L., Weng Z. (2003) ZDOCK Predictions for the CAPRI Challenge.
Proteins, 52:68-73
73. Chen R., Mintseris J., Janin J., Weng Z. (2003) A Protein-Protein Docking Benchmark. Proteins, 52:88-
91
74. Chen R., Weng Z. (2003) A Novel Shape Complementarity Scoring Function For Protein-Protein
Docking. Proteins, 51:397-408
75. Chen R., Weng Z. (2002) Docking Unbound Proteins Using Shape Complementarity, Desolvation, and
Electorstatics. Proteins, 47:281-294
76. Chen R., Xu YZ, Wu J,Pu Z, Jin SW, Liu WY, Xia ZX (1999) Purification and Characterization of
Trichomaglin-A Novel Ribosomal-inactivating Protein with Abortificient Activity. Biochem. Mol. Biol.
Int. 47:185-93
77. Wang XQ, Chen R., Wang YL, He TJ, Liu FC (1998) Theoretical Studies on Electrocompression of
Electrodeposited Halid Monolayer on Au(111) Surface. J. Phys. Chem. B 102:7568-76
Patents and Software
• Patent: methods and composition for monitoring an allograft recipient for a rejection response
(61/152199, PCT/US 10/24023)
• Patent: self organizing map in clinical diagnostics (11/617303)
• Inventor for system and database for personalized medicine (VariMed), licensed to Personalis
Inc.
• Inventor for method to integrate population and familial haplotype phasing into estimates of
genome-wide genetic of gene product risk, licensed to Personalis Inc.
• Inventor for software to identify differentially expressed conditions for a gene or set of genes,
licensed to Personalis Inc.
• Inventor for protein docking software ZDOCK & RDOCK, licensed to Accelrys Inc. with multi-
million dollar market
Invited Talks and Oral Presentations:
1. June 24, 2015, Invited Talk in Five Point Lecture Series in New York Genome Center, New
York, NY. Title: “Using Big Data to Interpret Genomes for Diagnosis, Therapeutics, and
Precision Medicine”.
2. May 21, 2015, Invited Talk in Functional Genomics & Predictive Medicine, Boston, MA. Title:
“Searching for Protective Alleles as Therapeutic Targets in Genomes with Electronic Medical
Records”.
3. May 5, 2015. Section Chair and Invited Talk in Biomarkers & Diagnostics World Congress
2015, Philadelphia, PA. Talk Title: “Using Big Data to Interpret Genomes for Disease Variant
Discovery, Precision Medicine and Novel Therapeutics”.
4. April 1, 2015, Invited Talk in School of Life Science, Fudan University, Shanghai, China. Talk
Title: Using Big Data to Interpret Genomes for Diagnosis, Therapeutics, and Precision
Medicine”.
9. Rong Chen, Ph.D. 9
5. April 1, 2015, Invited Talk in School of Pharmacy, Fudan University, Shanghai, China. Talk
Title: “Using Big Data to Interpret Genomes for Diagnosis, Therapeutics, and Precision
Medicine”.
6. March 30, 2015, Invited Talk in Second Military Medical University, Shanghai, China. Talk
Title: “Genetic Landscape of Prostate Cancer in Chinese Population”.
7. March 3, 2015, Invited Talk in School of Medicine, Columbia University, New York, NY. Talk
Title: “Using Big Data to Interpret Genomes for Protective Alleles and Precision Medicine”.
8. December 13, 2014, Invited Talk in Inaugural Personalized Medicine Conference:
Implementation of Next Generation Sequencing into Clinical Care, Buffalo, NY. Title “Drug-
centric Personalized Cancer Therapy Report”.
9. October 20, 2014, Talk in The American Society of Human Genetics, San Diego, CA. Title
“Using Big Data to Interpret Personal Genome for Precision Medicine”.
10. August 20, 2014, Invited Talk in Next Generation Dx Summit Moving Assays to the Clinic,
Capital Hilton, Washington, DC. Title “Using Big Data to Interpret Personal Genome for
Precision Medicine and Novel Therapeutics”.
11. July 11, 2014, Invited Talk in World Transplant Congress, San Francisco, CA. Title: “Building
databases, genome repositories, and tools to interpret personal genomes for clinical diagnosis,
precision medicine, and preventative care”
12. Jan 30, 2014, Invited Talk in Clinical Genomics conference, Boston, MA. Title: “Driving
Personalized Medicine and Clinical Diagnosis Using Genome Sequencing, Exome Sequencing
and Integrative Genomics”
13. Jan 27, 2014, Invited Talk in The Children’s Hospital of Philadelphia, Philadelphia, PA. Title:
“A worldwide search for the resilient buffered from childhood genetic diseases as a means to
identify novel therapeutic and preventive interventions”
14. Mar. 4, 2013, Invited Talk in Automated Personal Genome Analysis for Clinical Advisors:
Challenges and Solutions, Carnegie Mellon University, Pittsburgh, PA
15. Mar. 20, 2012, Oral presentation in 2012 AMIA Summit on Translational Bioinformatics (TBI),
San Francisco, CA. Title: “Quantifying multi-ethnic representation in genetic studies of high
mortality diseases”
16. Feb. 19, 2012, Invited talk in the 19th
International Molecular Medicine Tri-conference, San
Francisco, CA. Title: “Use public molecular measurements to drive the discovery of diagnostic
protein biomarkers”
17. Oct. 13, 2011, Oral presentation in 12th
International Congress of Human Genetics / American
Society of Human Genetics 61th annual meeting, Montreal, Canada. Title: “Type 2 diabetes risk
alleles show extreme directional differentiation among human populations, compared to other
diseases”
18. Sep. 14, 2011, Invited talk in Clinical Sequencing Standards Symposium in HL7, San Diego,
CA. Title: “Standardizing Genetic Reports for Medical Assessment of Personal Genome
Sequences”
19. Sep. 8, 2011, Session chair and Invited talk and session chair in Biomarker Discovery
Informatics, Philadelphia, PA. Title: “Using Public Molecular Measurements to Drive
Biomarker Discovery”
20. Apr. 14, 2011, Session chair and Invited talk and session chair in BioIT World Conference,
Boston, MA. Title: “Using Systems Medicine to Transform Biomarker Discovery and
Personalized Medicine”
21. Apr. 12, 2011, Invited talk in Agios Pharmaceutical, Cambridge, MA. Title: “Using Systems
Medicine to Transform Biomarker Discovery and Personalized Medicine”
22. Mar. 18, 2011, Invited talk in 3rd
NIH / Scripps Genomics for Transplantation Symposium, San
Diego, CA. Title: “Using public molecular measurements to drive discover of biomarkers for
cross-organ transplant rejection”
10. Rong Chen, Ph.D.
10
23. Mar. 14, 2011, Invited talk in 2nd International Conference on Transplantomics and Biomarkers
in Organ Transplantation, Barcelona, Spain. Title: “The clinical utility of whole genome
sequencing”
24. Mar. 15, 2011, Oral presentation in 2nd International Conference on Transplantomics and
Biomarkers in Organ Transplantation, Barcelona, Spain. Title: “Differentially Expressed RNA
from Public Microarray Data Identifies Serum Protein Biomarkers for Cross-organ Transplant
Rejection and Other Conditions”.
25. Mar. 8, 2011, 2011 Oral presentation in AMIA Summit on Translational Bioinformatics, San
Francisco, CA. Title: “Non-synonymous and Synonymous Coding SNPs Show Similar
Likelihood and Effect Size of Human Disease Association”.
26. Feb. 27, 2011, Invited talk in Biomarkers for Brain Disorders: Challenges and Opportunities,
Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. Title: “Translating Publically-
available molecular Data into Diagnostics and Personalized Medicine”
27. Feb. 3, 2011, Invited talk by Complete Genomics in 12th annual Advances in Genome Biology
and Technology (AGBT), Marco Island, FL. Title: “Genetics explains the ethnic disparity of
incidence rate of Melanoma and Pancreatic cancer”.
28. Jan. 4, 2011, Oral presentation, Pacific Symposium on Biocomputing (PSB), Big island of
Hawaii. Title: “Is the Reference Human Genome a Good Representation of a Healthy Control
and Consensus?”
29. Jun. 11, 2010, Invited Lecture in 13th
Annual International Toronto Heart Summit, 21 Avenue
Rd, Toronto, Ontario, Canada. Title: “Bioinformatics Approaches Yielding Biomarkers for
Personalized Medicine”
30. Aug. 11, 2010, Invited talk in Xiameng University, Xiameng, Fujian, China. Title: “Translating
Publically-available molecular Data into Diagnostics and Personalized Medicine”
31. Mar. 9, 2009, Invited Talk in FDA / National Center for Toxicological Research, 3900 NCTR
Road, Jefferson, AR. Title: “Biomarker Discovery from Public Gene Expression Data”
32. May 12 2008, Invited Talk in Indiana University School of Medicine, Indianapolis, IN. Title:
“Differentially Expressed Genes are Most Likely to have Variants Associated With Disease”
33. Jun. 12, 2004, Invited Talk in Biogeometry workshop, ACM Symposium on Computational
Geometry, New York, NY. Title: “An Integrated Approach to Protein-Protein Docking”
34. Sep. 19, 2002, Invited Talk in First CAPRI Evaluation Meeting, Agelonde, La Londe-des-
Maures, France. Title: "ZDOCK Predictions for the CAPRI Challenge"
35. Jul. 25, 2002, Oral presentation in Boston University-Humboldt University Workshop, Boston,
MA. Title: "A Novel Shape Complementarity Scoring Function for Protein Docking"
36. Dec. 1, 2001, Invited Talk in Computational Genomics Conference, Baltimore, Maryland. Title:
"An Integrated Approach to Predictive Protein-protein Docking"