Genevestigator Training
|
|
- Emil Clarke
- 8 years ago
- Views:
Transcription
1 Genevestigator Training Gent, 6 November 2012 Philip Zimmermann, Nebion AG
2 Goals Get to know Genevestigator What Genevestigator is for For who Genevestigator was created How to use Genevestigator for your research
3 Background: our company NEBION AG Spin-off company from the Swiss Federal Institute of Technology Zurich (ETH) Founded in 2008 Product: Genevestigator Services: curation of proprietary data data analysis services
4 Number of datasets Value of public -omics data Thousands of -omics experiments have been published; soon millions! Highly specialized experiments Genome-wide coverage Wealth of information! Total number of datasets available in GEO e.g. Publicly available microarray studies
5 Problem with public -omics data Not systematically curated No annotation using controlled vocabularies No normalization No quality control Rudimentary sample descriptions Many annotation errors!!! Therefore: Not easily exploitable! Extensive curation needed Methods and tools for global exploration are lacking
6 OUR SOLUTION Quality control Normalization Annotation Search Engine 1. Professional biocuration of public data 2. Powerful search engine 3. User-friendly Web based tools
7 Interpreting your results Pathways, biological processes Networks Diseases GSEA, GO enrichment Literature Your results e.g. List of genes INTERPRETATION Compare with data from public and proprietary omics experiments. View/cluster expression by: - Tissue types, cell lines - Genotypes - Diseases, perturbations, cancers - etc.
8 Annotation ontologies mouse example Perturbations ontology Anatomy ontology SPACE Neoplasm ontology SPACE TIME CLINICAL PARAMETERS RESPONSE
9 Concept of meta-profiles
10 Deep data integration Proof of principle
11 Tissue type versus perturbations
12 Database content - overview Status: october 2013
13 Database content diseases 172 diseases from 28 disease areas cancer types and subtypes Human and animal models
14 Genevestigator website
15 Genevestigator is an online tool Website Java Client Application INTERNET Search Engine
16 Comparison with other products experiment Sample annotation via keywords Sample annotation with controlled vocabularies using ontologies proprietary public analysis of one or a few experiments Individual experiment normalization Combine results Global compendium normalization Search engine Analysis on deeply integrated data Genedata expressionist Qlucore Omics Explorer Partek, Omicsoft, etc. MeV, GenePattern, etc. Nextbio Oncomine Medisapiens Genelogic GENEVESTIGATOR
17 Application areas Functional genomics Bring gene expression into the context of thousands of conditions Find gene-gene and gene-condition associations Interpret lists of genes Target validation / drug repositioning Find out when, where, and in response to what a target is expressed Biomarker identification / validation Find genes highly specific for selected diseases or conditions
18 Demo
19 Analytical approach 1: Condition Search genes which conditions? Anatomy [space] Development [time] Stimulus / Mutation [response]
20 Case study 1 Drug repositioning Example of Glivec (Novartis) Glivec inhibits ABL (used for CML treatment) Glivec also inhibits KIT: in which conditions is this gene strongly up regulated? cell culture (107) non-cancer tissues (177) neoplasms (1040 / 850 subtypes)
21 Analytical approach 2: Gene Search conditions which genes? Anatomy [space] Development [time] Stimulus / Mutation [response]
22 Gene Search Identify genes that exhibit specific expression characteristics Anatomy Development Stimulus / Mutation
23 condition 1 condition 2 condition 3 condition 4 condition 5 condition 6 condition 7 condition 8 condition 9 condition 10 condition 11 condition 12 condition 13 condition 14 condition 15 condition 16 condition 17 Concept of gene search in Genevestigator gene 1 gene 2 gene 3 gene 4 gene 5 most biomarker search approaches look for the genes, which respond the most to a given condition gene 6 gene 7 gene 8 gene 9 gene 10 gene 11 gene 12 gene 13 gene 14 gene 15?? This condition may include multiple similar studies How these genes respond to other conditions is unknown, because they were not included into the analysis gene 16 gene 17
24 condition 1 condition 2 condition 3 condition 4 condition 5 condition 6 condition 7 condition 8 condition 9 condition 10 condition 11 condition 12 condition 13 condition 14 condition 15 condition 16 condition 17 Concept of gene search in Genevestigator gene 1 gene 2 gene 3 gene 4 gene 5 gene 6 gene 7 gene 8 gene 9 gene 10 gene 11 gene 12 gene 13 gene 14 gene 15 gene 16 gene 17 Genevestigator allows to find out how specific these genes are (Meta-Profile Analysis -> Stimulus/Mutation tools) Only few are responsive only to condition 9 (black arrows). All others are sensitive to one (grey arrows) or more other conditions.
25 condition 1 condition 2 condition 3 condition 4 condition 5 condition 6 condition 7 condition 8 condition 9 condition 10 condition 11 condition 12 condition 13 condition 14 condition 15 condition 16 condition 17 Concept of gene search in Genevestigator gene 3 gene 5 gene 7 gene 13 gene 17 gene 10 gene 2 gene 15 gene 9 gene 12 gene 4 gene 11 gene 16 gene 1 gene 6 gene 8 gene 14 The Genevestigator Biomarker Search tools identify genes that are specifically responsive to the chosen condition (they respond minimally to other conditions). These genes are not necessarily the ones with the strongest response to the chosen condition The Genevestigator Biomarker Search tools usually find other target candidates than classical tools, which analyze only a subset of experiments
26 condition 1 condition 2 condition 3 condition 4 condition 5 condition 6 condition 7 condition 8 condition 9 condition 10 condition 11 condition 12 condition 13 condition 14 condition 15 condition 16 condition 17 condition 18 condition 19 condition 20 condition 21 condition 22 condition 23 condition 24 condition 25 condition 26 condition 27 condition 28 condition 29 condition 30 condition 31 condition 32 condition 33 condition 34 condition 35 condition 36 condition 37 condition 38 condition 39 condition 40 condition 41 condition 42 condition 43 condition 44 condition 45 condition 46 condition 47 condition 48 condition 49 condition 50 condition 51 condition 52 condition 53 condition 54 condition 55 condition 56 condition 57 condition 58 condition 59 condition 60 condition 61 condition 62 condition 63 condition 64 condition 65 condition 66 condition 67 condition 68 condition 69 condition 70 condition 71 condition 72 condition 73 condition 74 condition 75 Concept of gene search in Genevestigator Imagine extending this to a much wider set of conditions you may find other conditions to which the set of genes respond target condition gene 3 gene 5 gene 7 gene 13 gene 17 gene 10 gene 2 gene 15 gene 9 gene 12 gene 4 gene 11 gene 16 gene 1 gene 6 gene 8 gene 14 other conditions to which the genes are responding
27 Example of co-regulation Similar mechanisms of action cause similar transcriptional effects target condition(s) Actinomycin-D vmyb Oncolytic herpes simplex virus Propiconazole Sapphyrin Echinomycin Cell cycle inhibition co-inducing conditions Chemical: ARC
28 Clustering tools Goal: to identify groups of genes that have similar expression characteristics Tools: Hierarchical clustering (with leaf ordering) Biclustering (BiMax algorithm)
29 RefGenes
30 RefGenes - validation Reference genes searched from a set of 197 mouse liver samples 4 candidates compared to 4 commonly used genes Validation experiment on mouse liver Experimental validation on 16 mouse liver samples (RT-qPCR) Selection using GeNorm genorm selection of the most stable reference genes within this experiment
31 RefGenes study experimental validation
32 RefGenes concept
33 RefGenes website
34 Summary Genevestigator is... A gene expression search engine High quality compendium of manually curated expression data The world s largest and growing collection of expression data A flexible software application (plug-in architecture) Web-based (Internet or Intranet) User-friendly and extremely fast
35 Summary: it s all about CONTEXT!
AGILENT S BIOINFORMATICS ANALYSIS SOFTWARE
ACCELERATING PROGRESS IS IN OUR GENES AGILENT S BIOINFORMATICS ANALYSIS SOFTWARE GENESPRING GENE EXPRESSION (GX) MASS PROFILER PROFESSIONAL (MPP) PATHWAY ARCHITECT (PA) See Deeper. Reach Further. BIOINFORMATICS
More informationSchool of Nursing. Presented by Yvette Conley, PhD
Presented by Yvette Conley, PhD What we will cover during this webcast: Briefly discuss the approaches introduced in the paper: Genome Sequencing Genome Wide Association Studies Epigenomics Gene Expression
More informationThomson Reuters Biomarker Solutions: Hepatitis C Treatment Biomarkers and special considerations in patients with Asthma
: Hepatitis C Treatment Biomarkers and special considerations in patients with Asthma Abstract This case study aims to demonstrate the process of biomarker identification and validation utilizing Thomson
More informationIngenuity Pathway Analysis (IPA )
ProductProfile Ingenuity Pathway Analysis (IPA ) For the analysis and interpretation of omics data IPA is a web-based software application for the analysis, integration, and interpretation of data derived
More informationProteinQuest user guide
ProteinQuest user guide 1. Introduction... 3 1.1 With ProteinQuest you can... 3 1.2 ProteinQuest basic version 4 1.3 ProteinQuest extended version... 5 2. ProteinQuest dictionaries... 6 3. Directions for
More informationLecture 11 Data storage and LIMS solutions. Stéphane LE CROM lecrom@biologie.ens.fr
Lecture 11 Data storage and LIMS solutions Stéphane LE CROM lecrom@biologie.ens.fr Various steps of a DNA microarray experiment Experimental steps Data analysis Experimental design set up Chips on catalog
More informationEuro-BioImaging European Research Infrastructure for Imaging Technologies in Biological and Biomedical Sciences
Euro-BioImaging European Research Infrastructure for Imaging Technologies in Biological and Biomedical Sciences WP11 Data Storage and Analysis Task 11.1 Coordination Deliverable 11.2 Community Needs of
More informationWhat s New in Pathway Studio Web 11.1
1 1 What s New in Pathway Studio Web 11.1 Elseiver is pleased to announce the release of Pathway Studio Web 11.1 for all database subscriptions (Mammal, Mammal+ChemEffect+DiseaseFx, Plant). This release
More informationJust the Facts: A Basic Introduction to the Science Underlying NCBI Resources
1 of 8 11/7/2004 11:00 AM National Center for Biotechnology Information About NCBI NCBI at a Glance A Science Primer Human Genome Resources Model Organisms Guide Outreach and Education Databases and Tools
More informationJustClust User Manual
JustClust User Manual Contents 1. Installing JustClust 2. Running JustClust 3. Basic Usage of JustClust 3.1. Creating a Network 3.2. Clustering a Network 3.3. Applying a Layout 3.4. Saving and Loading
More informationSIMCA 14 MASTER YOUR DATA SIMCA THE STANDARD IN MULTIVARIATE DATA ANALYSIS
SIMCA 14 MASTER YOUR DATA SIMCA THE STANDARD IN MULTIVARIATE DATA ANALYSIS 02 Value From Data A NEW WORLD OF MASTERING DATA EXPLORE, ANALYZE AND INTERPRET Our world is increasingly dependent on data, and
More informationDr Alexander Henzing
Horizon 2020 Health, Demographic Change & Wellbeing EU funding, research and collaboration opportunities for 2016/17 Innovate UK funding opportunities in omics, bridging health and life sciences Dr Alexander
More informationAnalysis of Illumina Gene Expression Microarray Data
Analysis of Illumina Gene Expression Microarray Data Asta Laiho, Msc. Tech. Bioinformatics research engineer The Finnish DNA Microarray Centre Turku Centre for Biotechnology, Finland The Finnish DNA Microarray
More informationTargeting Specific Cell Signaling Pathways for the Treatment of Malignant Peritoneal Mesothelioma
The Use of Kinase Inhibitors: Translational Lab Results Targeting Specific Cell Signaling Pathways for the Treatment of Malignant Peritoneal Mesothelioma Sheelu Varghese, Ph.D. H. Richard Alexander, M.D.
More informationUsing the Grid for the interactive workflow management in biomedicine. Andrea Schenone BIOLAB DIST University of Genova
Using the Grid for the interactive workflow management in biomedicine Andrea Schenone BIOLAB DIST University of Genova overview background requirements solution case study results background A multilevel
More informationSoftware Description Technology
Software applications using NCB Technology. Software Description Technology LEX Provide learning management system that is a central resource for online medical education content and computer-based learning
More informationDiscover more, discover faster. High performance, flexible NLP-based text mining for life sciences
Discover more, discover faster. High performance, flexible NLP-based text mining for life sciences It s not information overload, it s filter failure. Clay Shirky Life Sciences organizations face the challenge
More informationSoftware reviews. Expression Pro ler: A suite of web-based tools for the analysis of microarray gene expression data
Expression Pro ler: A suite of web-based tools for the analysis of microarray gene expression data DNA microarray analysis 1±3 has become one of the most widely used tools for the analysis of gene expression
More informationHierarchical Clustering Analysis
Hierarchical Clustering Analysis What is Hierarchical Clustering? Hierarchical clustering is used to group similar objects into clusters. In the beginning, each row and/or column is considered a cluster.
More informationDelivering the power of the world s most successful genomics platform
Delivering the power of the world s most successful genomics platform NextCODE Health is bringing the full power of the world s largest and most successful genomics platform to everyday clinical care NextCODE
More informationAnalysis of gene expression data. Ulf Leser and Philippe Thomas
Analysis of gene expression data Ulf Leser and Philippe Thomas This Lecture Protein synthesis Microarray Idea Technologies Applications Problems Quality control Normalization Analysis next week! Ulf Leser:
More informationToxiCat: Hybrid Named Entity Recognition services to support curation of the Comparative Toxicogenomic Database
ToxiCat: Hybrid Named Entity Recognition services to support curation of the Comparative Toxicogenomic Database Dina Vishnyakova 1,2, 4, *, Julien Gobeill 1,3,4, Emilie Pasche 1,2,3,4 and Patrick Ruch
More informationBig Data and Text Mining
Big Data and Text Mining Dr. Ian Lewin Senior NLP Resource Specialist Ian.lewin@linguamatics.com www.linguamatics.com About Linguamatics Boston, USA Cambridge, UK Software Consulting Hosted content Agile,
More informationLearning Predictive Models of Gene Dynamics. Nick Jones, Sumeet Agarwal
Learning Predictive Models of Gene Dynamics Nick Jones, Sumeet Agarwal An Aim of Systems Biology How about predicting what cells are going to do? Quantitatively predict the response of cells to multiple
More informationdixa a data infrastructure for chemical safety Jos Kleinjans Dept of Toxicogenomics Maastricht University
dixa a data infrastructure for chemical safety Jos Kleinjans Dept of Toxicogenomics Maastricht University Current protocol for chemical safety testing Short Term Tests for Genetic Toxicity Bacterial Reverse
More informationBIOINFORMATICS Supporting competencies for the pharma industry
BIOINFORMATICS Supporting competencies for the pharma industry ABOUT QFAB QFAB is a bioinformatics service provider based in Brisbane, Australia operating nationwide and internationally. QFAB was established
More informationCore Facility Genomics
Core Facility Genomics versatile genome or transcriptome analyses based on quantifiable highthroughput data ascertainment 1 Topics Collaboration with Harald Binder and Clemens Kreutz Project: Microarray
More informationBig Data Visualization for Genomics. Luca Vezzadini Kairos3D
Big Data Visualization for Genomics Luca Vezzadini Kairos3D Why GenomeCruzer? The amount of data for DNA sequencing is growing Modern hardware produces billions of values per sample Scientists need to
More informationA Primer of Genome Science THIRD
A Primer of Genome Science THIRD EDITION GREG GIBSON-SPENCER V. MUSE North Carolina State University Sinauer Associates, Inc. Publishers Sunderland, Massachusetts USA Contents Preface xi 1 Genome Projects:
More informationData Mining and Machine Learning in Bioinformatics
Data Mining and Machine Learning in Bioinformatics PRINCIPAL METHODS AND SUCCESSFUL APPLICATIONS Ruben Armañanzas http://mason.gmu.edu/~rarmanan Adapted from Iñaki Inza slides http://www.sc.ehu.es/isg
More informationQuantitative and Qualitative Systems Biotechnology: Analysis Needs and Synthesis Approaches
Quantitative and Qualitative Systems Biotechnology: Analysis Needs and Synthesis Approaches Vassily Hatzimanikatis Department of Chemical Engineering Northwestern University Current knowledge of biological
More informationONLINE TOOLS FOR PRESENTATION AND ANALYSIS
In: Oligonucleotide Array Sequence Analysis ISBN: 978-1-60456-542-3 Editors: M.K. Moretti and L.J. Rizzo, pp. 265-295 2008 Nova Science Publishers, Inc. Chapter 9 ONLINE TOOLS FOR PRESENTATION AND ANALYSIS
More informationlife science data mining
life science data mining - '.)'-. < } ti» (>.:>,u» c ~'editors Stephen Wong Harvard Medical School, USA Chung-Sheng Li /BM Thomas J Watson Research Center World Scientific NEW JERSEY LONDON SINGAPORE.
More informationPharmacology skills for drug discovery. Why is pharmacology important?
skills for drug discovery Why is pharmacology important?, the science underlying the interaction between chemicals and living systems, emerged as a distinct discipline allied to medicine in the mid-19th
More informationBBSRC TECHNOLOGY STRATEGY: TECHNOLOGIES NEEDED BY RESEARCH KNOWLEDGE PROVIDERS
BBSRC TECHNOLOGY STRATEGY: TECHNOLOGIES NEEDED BY RESEARCH KNOWLEDGE PROVIDERS 1. The Technology Strategy sets out six areas where technological developments are required to push the frontiers of knowledge
More informationCancer Genomics: What Does It Mean for You?
Cancer Genomics: What Does It Mean for You? The Connection Between Cancer and DNA One person dies from cancer each minute in the United States. That s 1,500 deaths each day. As the population ages, this
More informationGene expression analysis. Ulf Leser and Karin Zimmermann
Gene expression analysis Ulf Leser and Karin Zimmermann Ulf Leser: Bioinformatics, Wintersemester 2010/2011 1 Last lecture What are microarrays? - Biomolecular devices measuring the transcriptome of a
More informationMultiExperiment Viewer Quickstart Guide
MultiExperiment Viewer Quickstart Guide Table of Contents: I. Preface - 2 II. Installing MeV - 2 III. Opening a Data Set - 2 IV. Filtering - 6 V. Clustering a. HCL - 8 b. K-means - 11 VI. Modules a. T-test
More informationThought leaders in the life sciences industry
Biological analysis_layout 1 28/03/2012 12:21 Page 68 Biological analysis and interpretation for improved research outcomes In the last few years, technological advancements in the life sciences have changed
More informationGenomeSpace Architecture
GenomeSpace Architecture The primary services, or components, are shown in Figure 1, the high level GenomeSpace architecture. These include (1) an Authorization and Authentication service, (2) an analysis
More informationPODD. An Ontology Driven Architecture for Extensible Phenomics Data Management
PODD An Ontology Driven Architecture for Extensible Phenomics Data Management Gavin Kennedy Gavin Kennedy PODD Project Manager High Resolution Plant Phenomics Centre Canberra, Australia What is Plant Phenomics?
More informationSurvey of clinical data mining applications on big data in health informatics
Survey of clinical data mining applications on big data in health informatics Matthew Herland, Taghi M. Khoshgoftaar, and Randall Wald 劉 俊 成 Survey of clinical data mining applications on big data in health
More informationData integration is a feature that clearly expands the role of the GTL
Technical Components of the GTL Knowledgebase Data Integration Data integration is a feature that clearly expands the role of the GTL Knowledgebase (GKB) beyond an archive to a dynamic systems biology
More information> Semantic Web Use Cases and Case Studies
> Semantic Web Use Cases and Case Studies Case Study: Applied Semantic Knowledgebase for Detection of Patients at Risk of Organ Failure through Immune Rejection Robert Stanley 1, Bruce McManus 2, Raymond
More informationZFIN Anatomy Pages - 3 Great Reasons Why You Need to Use Them
ZFIN NEWS The Zebrafish Information Network http://zfin.org Volume 5, Number 1 Spring 2008 In this issue: Maximizing Data Impact (pg.1) (pg.1) Full Text publications (pg.3) Morpholino Database (MODB) and
More informationIntegrating DNA Motif Discovery and Genome-Wide Expression Analysis. Erin M. Conlon
Integrating DNA Motif Discovery and Genome-Wide Expression Analysis Department of Mathematics and Statistics University of Massachusetts Amherst Statistics in Functional Genomics Workshop Ascona, Switzerland
More informationMediSapiens Ltd. Bio-IT solutions for improving cancer patient care. Because data is not knowledge. 19th of March 2015
19th of March 2015 MediSapiens Ltd Because data is not knowledge Bio-IT solutions for improving cancer patient care Sami Kilpinen, Ph.D Co-founder, CEO MediSapiens Ltd Copyright 2015 MediSapiens Ltd. All
More informationSystematic discovery of regulatory motifs in human promoters and 30 UTRs by comparison of several mammals
Systematic discovery of regulatory motifs in human promoters and 30 UTRs by comparison of several mammals Xiaohui Xie 1, Jun Lu 1, E. J. Kulbokas 1, Todd R. Golub 1, Vamsi Mootha 1, Kerstin Lindblad-Toh
More informationPersonalized medicine in China s healthcare system
Personalized medicine in China s healthcare system Jingmin Kan, Sam Linsen Netherlands office for Science and Technology, Guangzhou and Shanghai, China Content PERSONALIZED MEDICINE 2 FOCUS AT THE INDIVIDUAL
More informationLeading Genomics. Diagnostic. Discove. Collab. harma. Shanghai Cambridge, MA Reykjavik
Leading Genomics Diagnostic harma Discove Collab Shanghai Cambridge, MA Reykjavik Global leadership for using the genome to create better medicine WuXi NextCODE provides a uniquely proven and integrated
More informationCenter for Causal Discovery (CCD) of Biomedical Knowledge from Big Data University of Pittsburgh Carnegie Mellon University Pittsburgh Supercomputing
Center for Causal Discovery (CCD) of Biomedical Knowledge from Big Data University of Pittsburgh Carnegie Mellon University Pittsburgh Supercomputing Center Yale University PIs: Ivet Bahar, Jeremy Berg,
More informationEric Engelhard, Ph.D. Director of Informatics Mouse Biology Program University of California, Davis
KOMPCluster: A Pattern Recognition and 3D Visualization System for Phenotyping Projects Eric Engelhard, Ph.D. Director of Informatics Mouse Biology Program University of California, Davis Overview Large,
More informationNIH Genomic Data Sharing (GDS) Policy Guidance Memo #2 1
MEMORANDUM TO: Principal Investigators and Research Staff DATE: 2/22/15 FROM: Anne Klibanski, MD, Partners Chief Academic Officer (CAO) Paul Anderson, MD, PhD, BWH CAO Harry Orf, PhD, MGH Sr. Vice President-Research
More informationValidation and Replication
Validation and Replication Overview Definitions of validation and replication Difficulties and limitations Working examples from our group and others Why? False positive results still occur. even after
More informationData deluge (and it s applications) Gianluigi Zanetti. Data deluge. (and its applications) Gianluigi Zanetti
Data deluge (and its applications) Prologue Data is becoming cheaper and cheaper to produce and store Driving mechanism is parallelism on sensors, storage, computing Data directly produced are complex
More informationCyTOF2. Mass cytometry system. Unveil new cell types and function with high-parameter protein detection
CyTOF2 Mass cytometry system Unveil new cell types and function with high-parameter protein detection DISCOVER MORE. IMAGINE MORE. MASS CYTOMETRY. THE FUTURE OF CYTOMETRY TODAY. Mass cytometry resolves
More informationcansar: integrated cancer knowledgebase
in partnership with cansar: integrated cancer knowledgebase Bissan Al-Lazikani Cancer Research UK Cancer Therapeutics Unit 10 th Dec 2013 Sharing knowledge for drug discovery Resource to effectively integrate
More informationA leader in the development and application of information technology to prevent and treat disease.
A leader in the development and application of information technology to prevent and treat disease. About MOLECULAR HEALTH Molecular Health was founded in 2004 with the vision of changing healthcare. Today
More informationVoluntary Genomic Data Submissions at the U.S. FDA
Voluntary Genomic Data Submissions at the U.S. FDA International Conference on Harmonization Chicago, IL November 9-10, 9 2005 Felix W. Frueh, PhD Associate Director for Genomics Office of Clinical Pharmacology
More informationIMPLEMENTING BIG DATA IN TODAY S HEALTH CARE PRAXIS: A CONUNDRUM TO PATIENTS, CAREGIVERS AND OTHER STAKEHOLDERS - WHAT IS THE VALUE AND WHO PAYS
IMPLEMENTING BIG DATA IN TODAY S HEALTH CARE PRAXIS: A CONUNDRUM TO PATIENTS, CAREGIVERS AND OTHER STAKEHOLDERS - WHAT IS THE VALUE AND WHO PAYS 29 OCTOBER 2015 DR. DIRK J. EVERS BACKGROUND TreatmentMAP
More informationA Genetic Analysis of Rheumatoid Arthritis
A Genetic Analysis of Rheumatoid Arthritis Introduction to Rheumatoid Arthritis: Classification and Diagnosis Rheumatoid arthritis is a chronic inflammatory disorder that affects mainly synovial joints.
More informationStrategies in data integration to predict fish susceptibility to toxicants
Strategies in data integration to predict fish susceptibility to toxicants Fernando Ortega and Francesco Falciani School of Biosciences The University of Birmingham NERC PGP Project Kevin Chipman Mark
More informationHow To Get A Grant From Kinesis
- The collaboration initiative to move drug candidates forward Introduction What are we offering? How? Why apply? Terms Background For grant applications and to attract venture capital start-up companies
More informationMethods for network visualization and gene enrichment analysis July 17, 2013. Jeremy Miller Scientist I jeremym@alleninstitute.org
Methods for network visualization and gene enrichment analysis July 17, 2013 Jeremy Miller Scientist I jeremym@alleninstitute.org Outline Visualizing networks using R Visualizing networks using outside
More informationBIOINF 525 Winter 2016 Foundations of Bioinformatics and Systems Biology http://tinyurl.com/bioinf525-w16
Course Director: Dr. Barry Grant (DCM&B, bjgrant@med.umich.edu) Description: This is a three module course covering (1) Foundations of Bioinformatics, (2) Statistics in Bioinformatics, and (3) Systems
More informationGC3 Use cases for the Cloud
GC3: Grid Computing Competence Center GC3 Use cases for the Cloud Some real world examples suited for cloud systems Antonio Messina Trieste, 24.10.2013 Who am I System Architect
More informationKinexus has an in-house inventory of lysates prepared from 16 human cancer cell lines that have been selected to represent a diversity of tissues,
Kinexus Bioinformatics Corporation is seeking to map and monitor the molecular communications networks of living cells for biomedical research into the diagnosis, prognosis and treatment of human diseases.
More informationR. Julian Preston NHEERL U.S. Environmental Protection Agency Research Triangle Park North Carolina. Ninth Beebe Symposium December 1, 2010
Low Dose Risk Estimation: The Changing Face of Radiation Risk Assessment? R. Julian Preston NHEERL U.S. Environmental Protection Agency Research Triangle Park North Carolina Ninth Beebe Symposium December
More informationProtein Protein Interaction Networks
Functional Pattern Mining from Genome Scale Protein Protein Interaction Networks Young-Rae Cho, Ph.D. Assistant Professor Department of Computer Science Baylor University it My Definition of Bioinformatics
More informationGuide for Data Visualization and Analysis using ACSN
Guide for Data Visualization and Analysis using ACSN ACSN contains the NaviCell tool box, the intuitive and user- friendly environment for data visualization and analysis. The tool is accessible from the
More informationHow many of you have checked out the web site on protein-dna interactions?
How many of you have checked out the web site on protein-dna interactions? Example of an approximately 40,000 probe spotted oligo microarray with enlarged inset to show detail. Find and be ready to discuss
More informationIntroduction To Real Time Quantitative PCR (qpcr)
Introduction To Real Time Quantitative PCR (qpcr) SABiosciences, A QIAGEN Company www.sabiosciences.com The Seminar Topics The advantages of qpcr versus conventional PCR Work flow & applications Factors
More informationApplying data integration into reconstruction of gene networks from micro
Applying data integration into reconstruction of gene networks from microarray data PhD Thesis Proposal Dipartimento di Informatica e Scienze dell Informazione Università degli Studi di Genova December
More informationUniversity of Glasgow - Programme Structure Summary C1G5-5100 MSc Bioinformatics, Polyomics and Systems Biology
University of Glasgow - Programme Structure Summary C1G5-5100 MSc Bioinformatics, Polyomics and Systems Biology Programme Structure - the MSc outcome will require 180 credits total (full-time only) - 60
More informationBig data, Genomics and Public Health: Big Data meets DNA
Big data, Genomics and Public Health: Big Data meets DNA Winston Hide, Harvard School of Public Health and Harvard Stem Cell Institute Critical Data - Secondary use of Big Data from Critical Care - January
More informationElectronic access to mouse tumor data: the Mouse Tumor Biology Database (MTB) project
1999 Oxford University Press Nucleic Acids Research, 1999, Vol. 27, No. 1 99 105 Electronic access to mouse tumor data: the Mouse Tumor Biology Database (MTB) project Carol J. Bult*, Debra M. Krupke and
More informationGenetic profiles in relation to sports: a databased approach
Genetic profiles in relation to sports: a databased approach NWO & FAPESP Sports & Healthy Living, Sao Paulo, March 23 2016 Peter Taschner, Professor Genome-based Health taschner@generade.nl Generade CoE
More informationBig Data. Tom Plunkett Senior Consultant
Big Data Tom Plunkett Senior Consultant 2 Copyright 2013, Oracle and/or its affiliates. All rights reserved. Big Data in Healthcare Find relationship between gene to cancer interaction Use Case Cross-referenced
More informationPublic-Private Partnerships in early phase clinical research: Spurring access to innovative therapeutics
EPAAC WP8 Research Forum - 2 July, Sofitel Hotel Europe, Brussels Public-Private Partnerships in early phase clinical research: Spurring access to innovative therapeutics JY Blay, Past President EORTC
More informationText Mining for Health Care and Medicine. Sophia Ananiadou Director National Centre for Text Mining www.nactem.ac.uk
Text Mining for Health Care and Medicine Sophia Ananiadou Director National Centre for Text Mining www.nactem.ac.uk The Need for Text Mining MEDLINE 2005: ~14M 2009: ~18M Overwhelming information in textual,
More informationThe Future of the Electronic Health Record. Gerry Higgins, Ph.D., Johns Hopkins
The Future of the Electronic Health Record Gerry Higgins, Ph.D., Johns Hopkins Topics to be covered Near Term Opportunities: Commercial, Usability, Unification of different applications. OMICS : The patient
More informationTRANSLATIONAL BIOINFORMATICS 101
TRANSLATIONAL BIOINFORMATICS 101 JESSICA D. TENENBAUM Department of Bioinformatics and Biostatistics, Duke University Durham, NC 27715 USA Jessie.Tenenbaum@duke.edu SUBHA MADHAVAN Innovation Center for
More informationExercise with Gene Ontology - Cytoscape - BiNGO
Exercise with Gene Ontology - Cytoscape - BiNGO This practical has material extracted from http://www.cbs.dtu.dk/chipcourse/exercises/ex_go/goexercise11.php In this exercise we will analyze microarray
More informationInSyBio BioNets: Utmost efficiency in gene expression data and biological networks analysis
InSyBio BioNets: Utmost efficiency in gene expression data and biological networks analysis WHITE PAPER By InSyBio Ltd Konstantinos Theofilatos Bioinformatician, PhD InSyBio Technical Sales Manager August
More informationGet More Value from Your Reference Data Make it Meaningful with TopBraid RDM
Get More Value from Your Reference Data Make it Meaningful with TopBraid RDM Bob DuCharme Data Governance and Information Quality Conference June 9 TopQuadrant Company Focus: TopQuadrant was founded in
More informationAutoimmunity and immunemediated. FOCiS. Lecture outline
1 Autoimmunity and immunemediated inflammatory diseases Abul K. Abbas, MD UCSF FOCiS 2 Lecture outline Pathogenesis of autoimmunity: why selftolerance fails Genetics of autoimmune diseases Therapeutic
More informationAn EVIDENCE-ENHANCED HEALTHCARE ECOSYSTEM for Cancer: I/T perspectives
An EVIDENCE-ENHANCED HEALTHCARE ECOSYSTEM for Cancer: I/T perspectives Chalapathy Neti, Ph.D. Associate Director, Healthcare Transformation, Shahram Ebadollahi, Ph.D. Research Staff Memeber IBM Research,
More informationGenomics Services @ GENterprise
Genomics Services @ GENterprise since 1998 Mainz University spin-off privately financed 6-10 employees since 2006 Genomics Services @ GENterprise Sequencing Service (Sanger/3730, 454) Genome Projects (Bacteria,
More informationBiophysical and biochemical mechanisms of the biological effects of mobile phone radiation
Biophysical and biochemical mechanisms of the biological effects of mobile phone radiation Dariusz Leszczynski Research Professor; STUK - Radiation and Nuclear Safety Authority Helsinki, Finland & Guangbiao
More informationClinical and research data integration: the i2b2 FSM experience
Clinical and research data integration: the i2b2 FSM experience Laboratory of Biomedical Informatics for Clinical Research Fondazione Salvatore Maugeri - FSM - Hospital, Pavia, italy Laboratory of Biomedical
More informationG E N OM I C S S E RV I C ES
GENOMICS SERVICES THE NEW YORK GENOME CENTER NYGC is an independent non-profit implementing advanced genomic research to improve diagnosis and treatment of serious diseases. capabilities. N E X T- G E
More informationComplexity and Scalability in Semantic Graph Analysis Semantic Days 2013
Complexity and Scalability in Semantic Graph Analysis Semantic Days 2013 James Maltby, Ph.D 1 Outline of Presentation Semantic Graph Analytics Database Architectures In-memory Semantic Database Formulation
More informationMYRIAD, HITACHI, ORACLE & FRIEDLI JOIN FORCES TO MAP THE ENTIRE HUMAN PROTEOME
FOR IMMEDIATE RELEASE MYRIAD, HITACHI, ORACLE & FRIEDLI JOIN FORCES TO MAP THE ENTIRE HUMAN PROTEOME - $185 Million Collaboration to Determine All Human Protein Interactions And Decipher Biochemical Pathways
More informationEuro-BioImaging European Research Infrastructure for Imaging Technologies in Biological and Biomedical Sciences
Euro-BioImaging European Research Infrastructure for Imaging Technologies in Biological and Biomedical Sciences WP11 Data Storage and Analysis Task 11.1 Coordination Deliverable 11.3 Selected Standards
More informationBioinformatics for cancer immunology and immunotherapy
Bioinformatics for cancer immunology and immunotherapy Zlatko Trajanoski Biocenter, Division for Bioinformatics Innsbruck Medical University Innrain 80, 6020 Innsbruck, Austria Email: zlatko.trajanoski@i-med.ac.at
More informationMetodi Numerici per la Bioinformatica
Metodi Numerici per la Bioinformatica Biclustering A.A. 2008/2009 1 Outline Motivation What is Biclustering? Why Biclustering and not just Clustering? Bicluster Types Algorithms 2 Motivations Gene expression
More informationOriginal article AnnotCompute: annotation-based exploration and meta-analysis of genomics experiments
Original article AnnotCompute: annotation-based exploration and meta-analysis of genomics experiments Jie Zheng 1, Julia Stoyanovich 2, Elisabetta Manduchi 1, Junmin Liu 1 and Christian J. Stoeckert Jr
More informationFind the signal in the noise
Find the signal in the noise Electronic Health Records: The challenge The adoption of Electronic Health Records (EHRs) in the USA is rapidly increasing, due to the Health Information Technology and Clinical
More informationSpecial report. Chronic Lymphocytic Leukemia (CLL) Genomic Biology 3020 April 20, 2006
Special report Chronic Lymphocytic Leukemia (CLL) Genomic Biology 3020 April 20, 2006 Gene And Protein The gene that causes the mutation is CCND1 and the protein NP_444284 The mutation deals with the cell
More informationVisualizing Networks: Cytoscape. Prat Thiru
Visualizing Networks: Cytoscape Prat Thiru Outline Introduction to Networks Network Basics Visualization Inferences Cytoscape Demo 2 Why (Biological) Networks? 3 Networks: An Integrative Approach Zvelebil,
More information