Master's Thesis - deep genomics: harnessing the power of deep neural networks...Enrico Busto
The human genome project [1], an international scientific research project with the goal of determining the sequence of nucleotide base pairs that make up human DNA, lasted roughly 15 years and cost $5 billion (adjusted for inflation). With the recent advances in genome sequencing technology, that cost has now reduced to a few hundreds dollars [2] and can be done overnight.
Being able to access this kind of information may have a deep impact on the way complex diseases are treated: physicians will shift from general-purpose treatments to specific ones, tailored on the individual patient’s genomic features.This approach is referred to as precision medicine.
There are however several caveats: first of all, due to the nature of the problem, knowledge of both the biomedical and the computer science domain are required in order to correctly approach it; second, unlike more classical scenarios such as image classification or object detection, it is much more difficult to determine the accuracy of the system due to the complex and multifactorial nature of complex diseases such as cancer and neurodegenerative diseases.
Moreover, a black box kind of solution is unlikely to be of any use, due to legal and ethical reasons: interpretability of the model is crucial more than ever.
The goal of this thesis is to explore the possibilities and the limits of techniques based on deep neural networks for the analysis of biomolecular data, experimenting with publicly available datasets.
Professor Carole Goble, University of Manchester, talks at the RIN "Research data: policies & behaviour" event as part of a series on Research Information in Transition.
Excited to share our vision for bioinformatics education available for students and researchers that want to apply advanced multi-omics integration and machine learning to large biomedical datasets. Practice and learn from real-life projects.
Master's Thesis - deep genomics: harnessing the power of deep neural networks...Enrico Busto
The human genome project [1], an international scientific research project with the goal of determining the sequence of nucleotide base pairs that make up human DNA, lasted roughly 15 years and cost $5 billion (adjusted for inflation). With the recent advances in genome sequencing technology, that cost has now reduced to a few hundreds dollars [2] and can be done overnight.
Being able to access this kind of information may have a deep impact on the way complex diseases are treated: physicians will shift from general-purpose treatments to specific ones, tailored on the individual patient’s genomic features.This approach is referred to as precision medicine.
There are however several caveats: first of all, due to the nature of the problem, knowledge of both the biomedical and the computer science domain are required in order to correctly approach it; second, unlike more classical scenarios such as image classification or object detection, it is much more difficult to determine the accuracy of the system due to the complex and multifactorial nature of complex diseases such as cancer and neurodegenerative diseases.
Moreover, a black box kind of solution is unlikely to be of any use, due to legal and ethical reasons: interpretability of the model is crucial more than ever.
The goal of this thesis is to explore the possibilities and the limits of techniques based on deep neural networks for the analysis of biomolecular data, experimenting with publicly available datasets.
Professor Carole Goble, University of Manchester, talks at the RIN "Research data: policies & behaviour" event as part of a series on Research Information in Transition.
Excited to share our vision for bioinformatics education available for students and researchers that want to apply advanced multi-omics integration and machine learning to large biomedical datasets. Practice and learn from real-life projects.
The OmicsLogic Genomics Program provides in-depth understanding of bioinformatics methods we will cover in the upcoming 2019 session: https://edu.t-bio.info/organizations/omicslogic-genomics-training-program/
Bioinformatics, Its Usage and Advantagesbioinformatt
Bioinformatics is one of the major and important fields of biological sciences. Although it is a new discipline; however, it is developing at much faster rate. There are so many experts that are associated with this field.
Uses of Artificial Intelligence in BioinformaticsPragya Pai
This presentation is about the usage of Artificial Intelligence in Bioinformatics. These slides give the basic knowledge about usage of Artificial Intelligence in Bioinformatics.
Mastering RNA-Seq (NGS Data Analysis) - A Critical Approach To Transcriptomic...Elia Brodsky
This workshop will address critical issues related to Transcriptomics data:
Processing raw Next Generation Sequencing (NGS) data:
1. Next Generation Sequencing data preprocessing:
Trimming technical sequences
Removing PCR duplicates
2. RNA-seq based quantification of expression levels:
Conventional pipelines (looking at known transcripts)
Identification of novel isoforms
Analysis of Expression Data Using Machine Learning:
3. Unsupervised analysis of expression data:
Principal Component Analysis
Clustering
4. Supervised analysis:
Differential expression analysis
Classification, gene signature construction
5. Gene set enrichment analysis
The workshop will include hands-on exercises utilizing public domain datasets:
breast cancer cell lines transcriptomic profiles (https://genomebiology.biomedcentral.com/articles/10.1186/gb-2013-14-10-r110),
patient-derived xenograft (PDX) mouse model of tumor and stroma transcriptomic profiles (http://www.oncotarget.com/index.php?journal=oncotarget&page=article&op=view&path[]=8014&path[]=23533), and
processed data from The Cancer Genome Atlas samples (https://cancergenome.nih.gov/).
Team: The workshops are designed by the researchers at the Tauber Bioinformatics Research Center at University of Haifa, Israel in collaboration with academic centers across the US. Technical support for the workshops is provided by the Pine Biotech team. https://edu.t-bio.info/a-critical-approach-to-transcriptomic-data-analysis/
Slides for a presentation I gave at Texting 4 Health (Stanford University, 2007). Provides a survey of three related research methods for mobile messaging: diary methods, Wizard of Oz techniques, and field experiments. Relevant both for design-oriented research and scientific research.
Introduction
Definition
History
Principle
Components of bioinformatics
Bioinformatics databases
Tools of bioinformatics
Applications of bioinformatics
Molecular medicine
Microbial genomics
Plant genomics
Animal genomics
Human genomics
Drug and vaccine designing
Proteomics
For studying biomolecular structures
In- silico testing
Conclusion
References
The OmicsLogic Genomics Program provides in-depth understanding of bioinformatics methods we will cover in the upcoming 2019 session: https://edu.t-bio.info/organizations/omicslogic-genomics-training-program/
Bioinformatics, Its Usage and Advantagesbioinformatt
Bioinformatics is one of the major and important fields of biological sciences. Although it is a new discipline; however, it is developing at much faster rate. There are so many experts that are associated with this field.
Uses of Artificial Intelligence in BioinformaticsPragya Pai
This presentation is about the usage of Artificial Intelligence in Bioinformatics. These slides give the basic knowledge about usage of Artificial Intelligence in Bioinformatics.
Mastering RNA-Seq (NGS Data Analysis) - A Critical Approach To Transcriptomic...Elia Brodsky
This workshop will address critical issues related to Transcriptomics data:
Processing raw Next Generation Sequencing (NGS) data:
1. Next Generation Sequencing data preprocessing:
Trimming technical sequences
Removing PCR duplicates
2. RNA-seq based quantification of expression levels:
Conventional pipelines (looking at known transcripts)
Identification of novel isoforms
Analysis of Expression Data Using Machine Learning:
3. Unsupervised analysis of expression data:
Principal Component Analysis
Clustering
4. Supervised analysis:
Differential expression analysis
Classification, gene signature construction
5. Gene set enrichment analysis
The workshop will include hands-on exercises utilizing public domain datasets:
breast cancer cell lines transcriptomic profiles (https://genomebiology.biomedcentral.com/articles/10.1186/gb-2013-14-10-r110),
patient-derived xenograft (PDX) mouse model of tumor and stroma transcriptomic profiles (http://www.oncotarget.com/index.php?journal=oncotarget&page=article&op=view&path[]=8014&path[]=23533), and
processed data from The Cancer Genome Atlas samples (https://cancergenome.nih.gov/).
Team: The workshops are designed by the researchers at the Tauber Bioinformatics Research Center at University of Haifa, Israel in collaboration with academic centers across the US. Technical support for the workshops is provided by the Pine Biotech team. https://edu.t-bio.info/a-critical-approach-to-transcriptomic-data-analysis/
Slides for a presentation I gave at Texting 4 Health (Stanford University, 2007). Provides a survey of three related research methods for mobile messaging: diary methods, Wizard of Oz techniques, and field experiments. Relevant both for design-oriented research and scientific research.
Introduction
Definition
History
Principle
Components of bioinformatics
Bioinformatics databases
Tools of bioinformatics
Applications of bioinformatics
Molecular medicine
Microbial genomics
Plant genomics
Animal genomics
Human genomics
Drug and vaccine designing
Proteomics
For studying biomolecular structures
In- silico testing
Conclusion
References
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.
Trans disciplinary research is a must for excellence in science by Prof. Moha...Prof. Mohamed Labib Salem
In this talk, Prof. Mohamed L. Salem presents the importance of having a center of excellence at each institute to enhance and foster scientific research and innovation.
1. Francis Cunningham
52 Morgan Rd – Buffalo, NY 14220 – 716.697.0839 – fcunnin3@u.rochester.edu
Last Updated: May 20, 2015
Biomedical Engineering Qualifications
• Extensive design experience gained through capstone Senior Design Project. Project includes research and
development of a working prototype for the solution of a problem presented by an otolaryngologist at URMC.
• Laboratory proficiency skills obtained through research and laboratory work with hair follicle stem cells at the
University at Buffalo, under supervision of Dr. Andreadis, as well as through laboratory components of coursework.
• Knowledge of FDA regulations and device classifications gained through capstone Senior Design Project seminars.
• Extensive statistical analysis knowledge obtained through investigating the effects of MMP13 on collagen I
structure in mammary tumors.
• Excellent verbal and written communication skills through senior design engineering project proposals and
presentations.
Biomedical Engineering, Honors, and Co-Curriculars
UNIVERSITY OF ROCHESTER ROCHESTER, NY
Bachelors of Science in Biomedical Engineering May 2015
• Cumulative GPA: 3.4 (out of 4.0). Dean’s List Fall 2011, Spring 2013, Fall 2014.
• Member of AEMB Biomedical Engineering Honor Society (2015) and the Order of the Engineer (2015)
• Concentrated in Cell and Tissue engineering, and a focus in Art History and Visual Culture.
• Activities: Engineers Without Borders (2011-present, Vice President 2012-2013), Varsity Track and Field (2011-
present), Member of Chi Phi Fraternity (President 2014-2015).
Selected Biomedical Engineering and Science Courses, Labs, and Projects
Fluid Dynamics, MATLAB, Biosystems and Circuits, Heat and Mass Transfer, Cell Biology, Biomaterials,
Thermodynamics, Quantitative Physiology, Biosensors Circuits and Instrumentation, Cell and Tissue Engineering
• Created a pressure-measuring device to investigate a hypothesis proposed by an otolaryngologist at URMC by
developing a working prototype to aid in the diagnosis of Muscle Tension Dysphonia. Tasks included extensive
background research of the voice disorder, development of product design, prototyping and testing the device in vivo
to collect pilot data. Presented at the Department of Otolaryngology Research Day (May 2015).
• Biosensors and instrumentation laboratory work including building biopotential amplifiers, isolation of
biopotentials, and some basic logic circuitry used in biopotential applications.
• Highlighted the effects of MMP13 on Collagen I structure in mammary tumors on mice through analysis using
MATLAB and statistical methods, presented in an in depth research paper.
• Designed and built a circuit with user interface to analyze neural impulses of crickets. Applied circuit and filter
design to filter noise, amplify signal, and convert the electrical impulses to an audio signal.
Research Experience
UNIVERSITY AT BUFFALO BUFFALO, NY
Research Assistant 2013-2014
• Aided in the investigation of the effect of Nanog expression in senescent bone marrow MSCs using cell culture
techniques, transfections, virus synthesis and several protein assay techniques.
• Experienced in basic laboratory procedures for biology and some biochemistry applications, including DNA
purification, gene cloning, some protein quantification and basic cell culture techniques.
Teaching Experience
UNIVERSITY OF ROCHESTER ROCHESTER, NY
Biosystems and Circuits Teaching Assistant 2014
• Running the laboratory component of class with graduate students, grading, and holding office hours weekly for
students.
