The document discusses plans to integrate gene and variant annotation services from MyGene.info and MyVariant.info into a unified BioThings API. It describes making the APIs serve linked data via JSON-LD to enable data aggregation. It also mentions increasing usage of MyGene.info and MyVariant.info, developing Python/R clients, and acknowledging funding support.
BioThings SDK: a toolkit for building high-performance data APIs in biologyChunlei Wu
This is from my talk at BOSC 2017.
What’s BioThings?
We use “BioThings” to refer to objects of any biomedical entity-type represented in the biological knowledge space, such as genes, genetic variants, drugs, chemicals, diseases, etc.
BioThings SDK
SDK represents “Software Development Kit”. BioThings SDK provides a Python-based toolkit to build high-performance data APIs (or web services) from a single data source or multiple data sources. It has the particular focus on building data APIs for biomedical-related entities, a.k.a “BioThings”, though it’s not necessarily limited to the biomedical scope. For any given “BioThings” type, BioThings SDK helps developers to aggregate annotations from multiple data sources, and expose them as a clean and high-performance web API.
BioThings API: Building a FAIR API Ecosystem for Biomedical KnowledgeChunlei Wu
My talk about BioThings API project at ISMB 2018 Chicago, as part of BD2K special session. BioThings API project provides a collection of high-performance APIs (MyGene.info, MyVariant.info, MyChem.info), an SDK for building a new biomedical API (BioThings SDK), and a JSON-LD and OpenAPI based solution for across-API interoperability and knowledge exploration.
Knowledge Assembly at Scale with Semantic and Probabilistic TechniquesConnected Data World
Szymon Klarman's slides from his lightning talk at Connected Data London. Szymon is a research fellow at the Brunel University, his talk highlighted the current climate of academia publishing and how to makes sense of this information explosion using Knowledge Graphs.
BioThings SDK: a toolkit for building high-performance data APIs in biologyChunlei Wu
This is from my talk at BOSC 2017.
What’s BioThings?
We use “BioThings” to refer to objects of any biomedical entity-type represented in the biological knowledge space, such as genes, genetic variants, drugs, chemicals, diseases, etc.
BioThings SDK
SDK represents “Software Development Kit”. BioThings SDK provides a Python-based toolkit to build high-performance data APIs (or web services) from a single data source or multiple data sources. It has the particular focus on building data APIs for biomedical-related entities, a.k.a “BioThings”, though it’s not necessarily limited to the biomedical scope. For any given “BioThings” type, BioThings SDK helps developers to aggregate annotations from multiple data sources, and expose them as a clean and high-performance web API.
BioThings API: Building a FAIR API Ecosystem for Biomedical KnowledgeChunlei Wu
My talk about BioThings API project at ISMB 2018 Chicago, as part of BD2K special session. BioThings API project provides a collection of high-performance APIs (MyGene.info, MyVariant.info, MyChem.info), an SDK for building a new biomedical API (BioThings SDK), and a JSON-LD and OpenAPI based solution for across-API interoperability and knowledge exploration.
Knowledge Assembly at Scale with Semantic and Probabilistic TechniquesConnected Data World
Szymon Klarman's slides from his lightning talk at Connected Data London. Szymon is a research fellow at the Brunel University, his talk highlighted the current climate of academia publishing and how to makes sense of this information explosion using Knowledge Graphs.
BioThings API: Building a FAIR API Ecosystem for Biomedical KnowledgeChunlei Wu
My talk at NCI's CBIIT speaker series:
https://wiki.nci.nih.gov/display/CBIITSpeakers/2019/01/02/Jan+16%2C+Chunlei+Wu%2C+BioThings+API
A companion blog post: https://ncip.nci.nih.gov/blog/the-network-of-biothings/
See more details about BioThings project at http://biothings.io.
Biothings APIs: high-performance bioentity-centric web servicesChunlei Wu
High performance web service API for gene and genetic variant annotations: MyGene.info and MyVariant.info, And a SDK for building same high-performance API for other biomedical data types ("biothings")
XAPI and Machine Learning for Patient / LearnerJessie Chuang
xAPI and Machine Learning can help us build "intelligent assistance" for patients and learners, but human-in-the-loop machine learning is important. We need good learning design from the beginning and as we return data to instructors and learners immediately, humans can give great inputs to this human-machine collaboration.
Xapi enabled mobile health system with context-awareness & recommendation eng...Jessie Chuang
1. XAPI is a very effective tool in enabling Apps to serve humanity ASAP, because it connects heterogeneous data immediately.
2. XAPI is about people working together. xAPI projects are really across domains collaboration.
3. XAPI is about connecting current technologies, instead of re-inventing wheels.(API’s power)
PMR metabolomics and transcriptomics database and its RESTful web APIs: A dat...Araport
PMR database is a community resource for deposition and analysis of metabolomics data and related transcriptomics data. PMR currently houses metabolomics data from over 25 species of eukaryotes. In this talk, we introduce PMRs RESTful web APIs for data sharing, and demonstrate its applications in research using Araport to provide Arabidopsis metabolomics data.
Rare Variant Analysis Workflows: Analyzing NGS Data in Large CohortsGolden Helix Inc
Analysis of rare variants for population-level data is becoming a more common component of genomic research. Whether using exome chips, whole-exome sequencing, or even whole-genome sequencing, rare variation analysis requires a unique analytic perspective.
In this presentation, we will review some of the tools available in SVS for large sequenced cohorts including summarization, visualization, and statistical analysis of rare variants using KBAC, CMC, and other methods.
Special attention will be given to useful functions available for download from the SVS scripts repository.
Health Datapalooza IV: June 3rd-4th, 2013
Open Government Data
Moderator:
George Thomas, Enterprise Architect, Office of the Chief Information Officer (CIO), U.S. Department of Health & Human Services
Speakers:
John Erickson, Director of Web Science Operations, Tetherless Word Constellation, Rensselaer Polytechnic Institute
James P. McCusker, Ph.D Student, Dept. of Computer Science, Rensselaer Polytechnic Institute
Mark Musen, Professor, Stanford University and Principal Investigator, National Center for Biomedical Ontologies
Natasha Noy, Senior Research Scientist, Stanford University and Executive Committee Member, National Center for Biomedical Ontologies
Michael Pendleton, Linked Open Data Manager, US Environmental Protection Agency
The session will open with an overview of trends affecting open data sharing, including ‘broad data’ challenges that emerge when application developers have millions of open government datasets available. We will explore issues of web-scale data discovery, rapid and potentially ad hoc integration, visualization, and analysis of partially modeled datasets as well as issues arising from combining different data use policies. We will present emerging solution standards and transitioning academic technologies, including innovative work conducted by the ‘Watson’ research group at Rensselaer Polytechnic Institute on using Watson as a ‘data advisor’. Panelists will synthesize session topics including optimal steps toward an open health knowledge graph facilitating ‘data liquidity’ (as defined by the ability to easily combine and refine data from disparate publishers). Panelists will discuss enabling the implementation of effective ‘lifting schemes’ by leveraging ‘collaboration without coordination’ processes to produce efficient data access techniques that drive innovative new application development tools, products, and services.
BioThings API: Building a FAIR API Ecosystem for Biomedical KnowledgeChunlei Wu
My talk at NCI's CBIIT speaker series:
https://wiki.nci.nih.gov/display/CBIITSpeakers/2019/01/02/Jan+16%2C+Chunlei+Wu%2C+BioThings+API
A companion blog post: https://ncip.nci.nih.gov/blog/the-network-of-biothings/
See more details about BioThings project at http://biothings.io.
Biothings APIs: high-performance bioentity-centric web servicesChunlei Wu
High performance web service API for gene and genetic variant annotations: MyGene.info and MyVariant.info, And a SDK for building same high-performance API for other biomedical data types ("biothings")
XAPI and Machine Learning for Patient / LearnerJessie Chuang
xAPI and Machine Learning can help us build "intelligent assistance" for patients and learners, but human-in-the-loop machine learning is important. We need good learning design from the beginning and as we return data to instructors and learners immediately, humans can give great inputs to this human-machine collaboration.
Xapi enabled mobile health system with context-awareness & recommendation eng...Jessie Chuang
1. XAPI is a very effective tool in enabling Apps to serve humanity ASAP, because it connects heterogeneous data immediately.
2. XAPI is about people working together. xAPI projects are really across domains collaboration.
3. XAPI is about connecting current technologies, instead of re-inventing wheels.(API’s power)
PMR metabolomics and transcriptomics database and its RESTful web APIs: A dat...Araport
PMR database is a community resource for deposition and analysis of metabolomics data and related transcriptomics data. PMR currently houses metabolomics data from over 25 species of eukaryotes. In this talk, we introduce PMRs RESTful web APIs for data sharing, and demonstrate its applications in research using Araport to provide Arabidopsis metabolomics data.
Rare Variant Analysis Workflows: Analyzing NGS Data in Large CohortsGolden Helix Inc
Analysis of rare variants for population-level data is becoming a more common component of genomic research. Whether using exome chips, whole-exome sequencing, or even whole-genome sequencing, rare variation analysis requires a unique analytic perspective.
In this presentation, we will review some of the tools available in SVS for large sequenced cohorts including summarization, visualization, and statistical analysis of rare variants using KBAC, CMC, and other methods.
Special attention will be given to useful functions available for download from the SVS scripts repository.
Health Datapalooza IV: June 3rd-4th, 2013
Open Government Data
Moderator:
George Thomas, Enterprise Architect, Office of the Chief Information Officer (CIO), U.S. Department of Health & Human Services
Speakers:
John Erickson, Director of Web Science Operations, Tetherless Word Constellation, Rensselaer Polytechnic Institute
James P. McCusker, Ph.D Student, Dept. of Computer Science, Rensselaer Polytechnic Institute
Mark Musen, Professor, Stanford University and Principal Investigator, National Center for Biomedical Ontologies
Natasha Noy, Senior Research Scientist, Stanford University and Executive Committee Member, National Center for Biomedical Ontologies
Michael Pendleton, Linked Open Data Manager, US Environmental Protection Agency
The session will open with an overview of trends affecting open data sharing, including ‘broad data’ challenges that emerge when application developers have millions of open government datasets available. We will explore issues of web-scale data discovery, rapid and potentially ad hoc integration, visualization, and analysis of partially modeled datasets as well as issues arising from combining different data use policies. We will present emerging solution standards and transitioning academic technologies, including innovative work conducted by the ‘Watson’ research group at Rensselaer Polytechnic Institute on using Watson as a ‘data advisor’. Panelists will synthesize session topics including optimal steps toward an open health knowledge graph facilitating ‘data liquidity’ (as defined by the ability to easily combine and refine data from disparate publishers). Panelists will discuss enabling the implementation of effective ‘lifting schemes’ by leveraging ‘collaboration without coordination’ processes to produce efficient data access techniques that drive innovative new application development tools, products, and services.
In this talk at the CECAM 2015 Workshop on Future Technologies in Automated Atomistic Simulations, I will discuss the Materials Project Ecosystem, an initiative to develop a comprehensive set of open-source software and data tools for materials informatics. The Materials Project is a US Department of Energy-funded initiative to make the computed properties of all known inorganic materials publicly available to all materials researchers to accelerate materials innovation. Today, the Materials Project database boasts more than 58,000 materials, covering a broad range of properties, including energetic properties (e.g., phase and aqueous stability, reaction energies), electronic structure (bandstructures, DOSs) and structural and mechanical properties (e.g., elastic constants).
A linchpin of the Materials Project is its robust data and software infrastructure, built on best open-source software development practices such as continuous testing and integration, and comprehensive documentation. I will provide an overview of the open-source software modules that have been developed for materials analysis (Python Materials Genomics), error handling (Custodian) and scientific workflow management (FireWorks), as well as the Materials API, a first-of-its-kind interface for accessing materials data based on REpresentational State Transfer (REST) principles. I will show a materials researcher may use and build on these software and data tools for materials informatics as well as to accelerate his own research.
Presentaion for NetBio SIG 2013 by Robin Haw, Scientific Associate and Outreach Coordinator, Ontario Institute for Cancer Research. “Reactome Knowledgebase and Functional Interaction (FI) Cytoscape Plugin”
Bio-IT 2017 - Session 7: Next-Gen Sequencing InformaticsYaoyu Wang
WebMeV is a robust, open-source cloud based scalable data analysis software tool developed at the Dana-Farber Cancer Institute that uses intuitive visual interfaces to provide users with access to advanced data analysis methods. It will allow researchers and biotechnology companies considering tools for large scale genomic data analysis an alternative option to all the proprietary software.
Richard's entangled aventures in wonderlandRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
Comparing Evolved Extractive Text Summary Scores of Bidirectional Encoder Rep...University of Maribor
Slides from:
11th International Conference on Electrical, Electronics and Computer Engineering (IcETRAN), Niš, 3-6 June 2024
Track: Artificial Intelligence
https://www.etran.rs/2024/en/home-english/
What is greenhouse gasses and how many gasses are there to affect the Earth.moosaasad1975
What are greenhouse gasses how they affect the earth and its environment what is the future of the environment and earth how the weather and the climate effects.
(May 29th, 2024) Advancements in Intravital Microscopy- Insights for Preclini...Scintica Instrumentation
Intravital microscopy (IVM) is a powerful tool utilized to study cellular behavior over time and space in vivo. Much of our understanding of cell biology has been accomplished using various in vitro and ex vivo methods; however, these studies do not necessarily reflect the natural dynamics of biological processes. Unlike traditional cell culture or fixed tissue imaging, IVM allows for the ultra-fast high-resolution imaging of cellular processes over time and space and were studied in its natural environment. Real-time visualization of biological processes in the context of an intact organism helps maintain physiological relevance and provide insights into the progression of disease, response to treatments or developmental processes.
In this webinar we give an overview of advanced applications of the IVM system in preclinical research. IVIM technology is a provider of all-in-one intravital microscopy systems and solutions optimized for in vivo imaging of live animal models at sub-micron resolution. The system’s unique features and user-friendly software enables researchers to probe fast dynamic biological processes such as immune cell tracking, cell-cell interaction as well as vascularization and tumor metastasis with exceptional detail. This webinar will also give an overview of IVM being utilized in drug development, offering a view into the intricate interaction between drugs/nanoparticles and tissues in vivo and allows for the evaluation of therapeutic intervention in a variety of tissues and organs. This interdisciplinary collaboration continues to drive the advancements of novel therapeutic strategies.
Deep Behavioral Phenotyping in Systems Neuroscience for Functional Atlasing a...Ana Luísa Pinho
Functional Magnetic Resonance Imaging (fMRI) provides means to characterize brain activations in response to behavior. However, cognitive neuroscience has been limited to group-level effects referring to the performance of specific tasks. To obtain the functional profile of elementary cognitive mechanisms, the combination of brain responses to many tasks is required. Yet, to date, both structural atlases and parcellation-based activations do not fully account for cognitive function and still present several limitations. Further, they do not adapt overall to individual characteristics. In this talk, I will give an account of deep-behavioral phenotyping strategies, namely data-driven methods in large task-fMRI datasets, to optimize functional brain-data collection and improve inference of effects-of-interest related to mental processes. Key to this approach is the employment of fast multi-functional paradigms rich on features that can be well parametrized and, consequently, facilitate the creation of psycho-physiological constructs to be modelled with imaging data. Particular emphasis will be given to music stimuli when studying high-order cognitive mechanisms, due to their ecological nature and quality to enable complex behavior compounded by discrete entities. I will also discuss how deep-behavioral phenotyping and individualized models applied to neuroimaging data can better account for the subject-specific organization of domain-general cognitive systems in the human brain. Finally, the accumulation of functional brain signatures brings the possibility to clarify relationships among tasks and create a univocal link between brain systems and mental functions through: (1) the development of ontologies proposing an organization of cognitive processes; and (2) brain-network taxonomies describing functional specialization. To this end, tools to improve commensurability in cognitive science are necessary, such as public repositories, ontology-based platforms and automated meta-analysis tools. I will thus discuss some brain-atlasing resources currently under development, and their applicability in cognitive as well as clinical neuroscience.
A brief information about the SCOP protein database used in bioinformatics.
The Structural Classification of Proteins (SCOP) database is a comprehensive and authoritative resource for the structural and evolutionary relationships of proteins. It provides a detailed and curated classification of protein structures, grouping them into families, superfamilies, and folds based on their structural and sequence similarities.
Cancer cell metabolism: special Reference to Lactate PathwayAADYARAJPANDEY1
Normal Cell Metabolism:
Cellular respiration describes the series of steps that cells use to break down sugar and other chemicals to get the energy we need to function.
Energy is stored in the bonds of glucose and when glucose is broken down, much of that energy is released.
Cell utilize energy in the form of ATP.
The first step of respiration is called glycolysis. In a series of steps, glycolysis breaks glucose into two smaller molecules - a chemical called pyruvate. A small amount of ATP is formed during this process.
Most healthy cells continue the breakdown in a second process, called the Kreb's cycle. The Kreb's cycle allows cells to “burn” the pyruvates made in glycolysis to get more ATP.
The last step in the breakdown of glucose is called oxidative phosphorylation (Ox-Phos).
It takes place in specialized cell structures called mitochondria. This process produces a large amount of ATP. Importantly, cells need oxygen to complete oxidative phosphorylation.
If a cell completes only glycolysis, only 2 molecules of ATP are made per glucose. However, if the cell completes the entire respiration process (glycolysis - Kreb's - oxidative phosphorylation), about 36 molecules of ATP are created, giving it much more energy to use.
IN CANCER CELL:
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
introduction to WARBERG PHENOMENA:
WARBURG EFFECT Usually, cancer cells are highly glycolytic (glucose addiction) and take up more glucose than do normal cells from outside.
Otto Heinrich Warburg (; 8 October 1883 – 1 August 1970) In 1931 was awarded the Nobel Prize in Physiology for his "discovery of the nature and mode of action of the respiratory enzyme.
WARNBURG EFFECT : cancer cells under aerobic (well-oxygenated) conditions to metabolize glucose to lactate (aerobic glycolysis) is known as the Warburg effect. Warburg made the observation that tumor slices consume glucose and secrete lactate at a higher rate than normal tissues.
Nutraceutical market, scope and growth: Herbal drug technologyLokesh Patil
As consumer awareness of health and wellness rises, the nutraceutical market—which includes goods like functional meals, drinks, and dietary supplements that provide health advantages beyond basic nutrition—is growing significantly. As healthcare expenses rise, the population ages, and people want natural and preventative health solutions more and more, this industry is increasing quickly. Further driving market expansion are product formulation innovations and the use of cutting-edge technology for customized nutrition. With its worldwide reach, the nutraceutical industry is expected to keep growing and provide significant chances for research and investment in a number of categories, including vitamins, minerals, probiotics, and herbal supplements.
Astronomy Update- Curiosity’s exploration of Mars _ Local Briefs _ leadertele...
Chunlei wu heart_bd2k_201602_ebi
1. Chunlei Wu, Ph.D.
cwu@scripps.edu
@chunleiwu
Associate Professor of Molecular Medicine
Dept. of Molecular Experimental Medicine
The Scripps Research Institute
La Jolla, CA, USA
02/23/2016
HeartBD2K PI meeting at EBI
Integrated Annotation Services for "BioThings"
From MyGene.info and MyVariant.info towards BioThings API
7. MyVariant.info for the end users:
http://MyVariant.info
(currently v1 API, two endpoints)
http://MyVariant.info/v1/query?q=<query>
any query term(s)
matching variant hits
http://MyVariant.info/v1/variant/<variantid>
hgvs id(s)
matching variant object(s)
Both supports batch-mode via POST
Simple API. No sign-up. No API key.
Try our live API , and documentations
8. MyGene.info for the end users:
http://MyGene.info
(currently v2 API, two endpoints)
http://MyGene.info/v2/query?q=<query>
any query term(s)
matching gene hits
http://MyGene.info/v2/gene/<geneid>
gene id(s)
matching gene object(s)
Both supports batch-mode via POST
Simple API. No sign-up. No API key.
Try our live API , and documentations
14. MyVariant.info official Python/R Clients
myvariant Python client hosted in PyPI
(initial release in Aug 2015)
myvariant R client hosted in Bioconductor
(initial release in Oct 2015)
24. Acknowledgement
Funding and Support
U54GM114833
U01HG008473
Washington U:
Ben Ainscough
Obi Griffith
TSRI:
Andrew Su
Jiwen Xin
Cyrus Afrasiabi
Ginger Tsueng
Adam Mark
Greg Stupp
Tim Putman
STSI:
Eric Topol
Ali Torkamani
Galina Erikson
U. Washington:
Sean Mooney
Moritz Juchler
Nikhil Gopal
OICR:
Robin Haw
UC Berkeley:
Chris Mungall
UCSD:
Trish Whetzel
MyVariant.info MyGene.info
Editor's Notes
A high-performance query engine for aggregated variant annotations.
Annotation data are fundamental
Gene anno: no need a slide to explain, everyone need them
Var anno: relatively new, more and more trending due to the booming of NGS
