A brief introduction to Cytoscape

Size: px
Start display at page:

Download "A brief introduction to Cytoscape"

Transcription

1 A brief introduction to Cytoscape Scientific day «Data mining of omics data» 5th Feb 2015 CGFB, Bordeaux (U1038, EDyP team, CEA-Grenoble)

2 OUTLINES Concepts and context Cytoscape features Demo: a real «use-case» (PI3K-mTOR pathway)

3 Le data mining: plus qu un domaine, une démarche (1) accès aux données, stockées sous une forme structurée (BD, fichiers tabulaires) ou non-structurée (texte, image, etc.); (2) la préparation des données, en vue du traitement; (3) l'utilisation de techniques de fouille de données, issues de la statistique ou de l'apprentissage automatique; (4) évaluer et valider les connaissances extraites; (5) déploiement des connaissances en vue d'une utilisation effective. From Fayyad, 1996

4 Data mining in the context of MS-based proteomics analysis Käll L, Vitek O PLoS Comput Biol

5 Some types biomolecular networks Gene regulatory networks Metabolic networks PPI networks Signaling networks ChiP-chip/ChIP-seq Gene expression data Sequence Classical biochemistry MS Isotope labeling Yeast two-hybrid MS Pull-down PTM measurements Networks of functional links Networks of genetic interactions Sequence similarity Expression data Large-scale synthetic interaction or mutants studies

6 In the «omics» field, a pressing need for: analyzing integration visualization browsing querying editing (annotation) F60-64 env13 ZT50 es4075 MaxEnt 3 8 [Ev-36586,It50,En1] (0.050,200.00,0.200, ,2,Cmp) 1: TOF MSMS ES+ 100 % 0 (596.29) F G L (329.16) ymax y b y1 y M/z

7 Data integration and visualization Protein phenotype: are essential proteins more connected? Lethal Viable The most highly connected proteins in the cell are the most important for its survival. Jeong et al, 2001, Nature revisited by C. Hermann (TAGC, Luminy, FR)

8 Data integration for knowledge extraction Merico et al, Nat. Biotech, 2009 Functional inference from the context («Guilt-by-association principle»): subcellular localization, expression level and coexpression => Psf1, 2, 3 DNA replication / Cse4, multifonctional / Orc1-6, interconnected complex

9 Cline et al, Nature Protocols 2007

10 Import data from a variety of sources (public repositories, databases, in-house ) Visualize interaction networks Extract useful information

11 Visualization by using graph representation Linear Graph How many interactions involve YHR105W? Are YHR105W and Pep12 «close»? From B. Schwikowski

12 One graph, many drawings and different formalisms

13 Cytoscape data model - Network (Graph) Nodes Edges - Attributes From B. Schwikowski

14 Cytoscape core functionality: Integrating data - No hardcoded Semantics (generic) -A variety of data can be combined From B. Schwikowski

15 The Cytoscape desktop

16 Data import: various formats

17 Data export: various formats Standards format and graphical too!

18 Interaction file sample: Cytoscape I/O: Plain-text data import Network data format (.sif) Node attribute file (.noa) Edge attribute file (.eda) Expression data file format (tab):

19 Import your own network (tabulated or excel files) PI3-kinase pathway Y2H experiment Pilot-Strock et al, MCP, 2010

20 Data import-export: edges attributes

21 Import your own network: map nodes attributes 1 Primary key! 2

22 Cytoscape core functionality: VizMapper mappings Continuous mapping (numerical values) Discrete mapping

23 Cytoscape core functionality: VizMapper Map network attributes to node/edges visual properties

24 Cytoscape core functionality: VizMapper Create your visual style (advanced): e.g. node size according to p-val, edge thickness according to co-expression strength Co-expression graph visualization Doustaly et al, Metallomics, 2014

25 Graph-layout algorithm: arrange your network Circular: not very informative Hierarchical: tree structure Organic: generally more intuitive

26 Cytoscape layout with attributes Group attributes layout: e.g. molecular function (nodes) ~ signalling pathways (group)

27 Cytoscape core functionality: filters Query: search proteins annotated as «unknown» function 1 Build your query 2 Check results

28 Cytoscape core functionality: browsing nodes

29 Cytoscape extended functionality: plugins

30 Cytoscape plugins classification Saito et al, 2012, Nature Methods

31 Cytoscape: Network analysis workflow Saito et al, 2012, Nature Methods

32 Examples of plugin outputs Saito et al, 2012, Nature Methods

33 Cytoscape demo: PI3K/mTOR network Mol Cell Proteomics Jul;9(7):

34 PI3K-mTOR pathway (Pilot-Storck et al.)

35 METHODOLOGY & RESULTS (Pilot-Storck et al.) -Two stringent Y2H screens were carried out in E10.5 mouse embryo library and human ORFeome v1.1 ORF library. -To validate Y2H interactions, protein-protein interactions (PPIs) were tested by co-affinity purification (co-ap) assays in human HEK293T cells. -Manual curation of the literature (*) for binary interactions for each PI3KmTOR component was performed. * BIND, MINT, HPRD, APID and Pubmed databases. E10.5 mouse embryo library: 68 protein-protein interactions (PPIs) - human ORFeome v1.1 ORF library: 8 PPIs -91% were new interactions -These PPIs involved 15 out of 34 PI3K-mTOR pathway tested components - Low overlap between literature and screens (only 7 PPIs in common): * Sampling and Assay sensitivity * Kinases subcellular localization (lipid binding domains) * Kinase activaty (GSK3 example) - literature curation and our screens provide an interactome of 802 interactions for the PI3K-mTOR pathway DEMO!

36 Cytoscape - key points Key features - import data from a variety of sources (in-house, PSICQUIC-UC, Entrez ) - Visualize interaction networks - Extract useful observations (clustermaker, Bingo, JActive ) Modular environment (more than 150 plugins available today) Flexible without buit-in semantics (but ) Straightforward data model User community Well-supported & Active online tutorials: Free and open-source Just try it out!!

37 From experimental (raw) data to biological knowledge: a continuum First level: data qualification (how «trustable» is my dataset?) => biostatistics Experimental design (when conditions do apply) Statistics is «only» a tool that help decision Second level: data mining (knowledge extraction) => bioinformatics (from descriptive towards predictive approach) Quality of data sources: - score and threshold, level of biocuration - in-house expertise, guidelines, format jungle - workshop, survey Methods & tools: my data requires the right tool - Think before acting bioinformatic experiments should be designed as carefully than experimental ones bioinfo should not be considered as a one-click step - What can I do without any bioinfo people around? - expertise sharing -> training session / users club

38 References and useful links Cytoscape: a software environment for integrated models of biomolecular interaction networks. Shannon P et al., Genome Res (11): Integration of biological networks and gene expression data using Cytoscape. Cline MS et al., Nat Protoc (10): clustermaker: a multi-algorithm clustering plugin for Cytoscape. Morris JH, Apeltsin L, Newman AM, Baumbach J, Wittkop T, Su G, Bader GD, Ferrin TE. BMC Bioinformatics :436. Su G, Morris JH, Demchak B, Bader GD. Biological network exploration with cytoscape 3. Curr Protoc Bioinformatics Sep 8;47:8. PubMed PMID: ; URL: Cytoscape main website: Cytoscape wiki : Tutorials web portal:

39 From B. Schwikowski

Un (bref) aperçu des méthodes et outils de fouilles et de visualisation de données «omics»

Un (bref) aperçu des méthodes et outils de fouilles et de visualisation de données «omics» Un (bref) aperçu des méthodes et outils de fouilles et de visualisation de données «omics» Workshop «Protéomique & Maladies rares» 25 th September 2012, Paris yves.vandenbrouck@cea.fr CEA Grenoble irtsv

More information

Visualizing Networks: Cytoscape. Prat Thiru

Visualizing 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

TUTORIAL From Protein-Protein Interactions (PPIs) to networks and pathways ??? http://bioinfow.dep.usal.es

TUTORIAL From Protein-Protein Interactions (PPIs) to networks and pathways ??? http://bioinfow.dep.usal.es TUTORIAL From Protein-Protein Interactions (PPIs) to networks and pathways http://bioinfow.dep.usal.es Dr. Javier De Las Rivas (jrivas@usal.es) Dr. Carlos Prieto (cprietos@usal.es) Bioinformatics and Functional

More information

Protein Protein Interaction Networks

Protein 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 information

ProteinQuest user guide

ProteinQuest 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 information

BIOINF 525 Winter 2016 Foundations of Bioinformatics and Systems Biology http://tinyurl.com/bioinf525-w16

BIOINF 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 information

Tutorial for proteome data analysis using the Perseus software platform

Tutorial for proteome data analysis using the Perseus software platform Tutorial for proteome data analysis using the Perseus software platform Laboratory of Mass Spectrometry, LNBio, CNPEM Tutorial version 1.0, January 2014. Note: This tutorial was written based on the information

More information

Protein Protein Interactions (PPI) APID (Agile Protein Interaction DataAnalyzer)

Protein Protein Interactions (PPI) APID (Agile Protein Interaction DataAnalyzer) APID (Agile Protein Interaction DataAnalyzer) 23 APID (Agile Protein Interaction DataAnalyzer) Integrates and unifies 7 DBs: BIND, DIP, HPRD, IntAct, MINT, BioGRID. Includes 51,873 proteins 241,204 interactions

More information

Exercise with Gene Ontology - Cytoscape - BiNGO

Exercise 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 information

Aiping Lu. Key Laboratory of System Biology Chinese Academic Society APLV@sibs.ac.cn

Aiping Lu. Key Laboratory of System Biology Chinese Academic Society APLV@sibs.ac.cn Aiping Lu Key Laboratory of System Biology Chinese Academic Society APLV@sibs.ac.cn Proteome and Proteomics PROTEin complement expressed by genome Marc Wilkins Electrophoresis. 1995. 16(7):1090-4. proteomics

More information

Lecture 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 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 information

Presenting data: how to convey information most effectively Centre of Research Excellence in Patient Safety 20 Feb 2015

Presenting data: how to convey information most effectively Centre of Research Excellence in Patient Safety 20 Feb 2015 Presenting data: how to convey information most effectively Centre of Research Excellence in Patient Safety 20 Feb 2015 Biomedical Informatics: helping visualization from molecules to population Dr. Guillermo

More information

Network Analysis. BCH 5101: Analysis of -Omics Data 1/34

Network Analysis. BCH 5101: Analysis of -Omics Data 1/34 Network Analysis BCH 5101: Analysis of -Omics Data 1/34 Network Analysis Graphs as a representation of networks Examples of genome-scale graphs Statistical properties of genome-scale graphs The search

More information

NeXO Web: the NeXO ontology database and visualization platform

NeXO Web: the NeXO ontology database and visualization platform Nucleic Acids Research Advance Access published November 23, 2013 Nucleic Acids Research, 2013, 1 6 doi:10.1093/nar/gkt1192 NeXO Web: the NeXO ontology database and visualization platform Janusz Dutkowski*,

More information

CENG 734 Advanced Topics in Bioinformatics

CENG 734 Advanced Topics in Bioinformatics CENG 734 Advanced Topics in Bioinformatics Week 9 Text Mining for Bioinformatics: BioCreative II.5 Fall 2010-2011 Quiz #7 1. Draw the decompressed graph for the following graph summary 2. Describe the

More information

Introduction to Proteomics 1.0

Introduction to Proteomics 1.0 Introduction to Proteomics 1.0 CMSP Workshop Tim Griffin Associate Professor, BMBB Faculty Director, CMSP Objectives Why are we here? For participants: Learn basics of MS-based proteomics Learn what s

More information

REGULATIONS FOR THE DEGREE OF BACHELOR OF SCIENCE IN BIOINFORMATICS (BSc[BioInf])

REGULATIONS FOR THE DEGREE OF BACHELOR OF SCIENCE IN BIOINFORMATICS (BSc[BioInf]) 820 REGULATIONS FOR THE DEGREE OF BACHELOR OF SCIENCE IN BIOINFORMATICS (BSc[BioInf]) (See also General Regulations) BMS1 Admission to the Degree To be eligible for admission to the degree of Bachelor

More information

PPInterFinder A Web Server for Mining Human Protein Protein Interaction

PPInterFinder A Web Server for Mining Human Protein Protein Interaction PPInterFinder A Web Server for Mining Human Protein Protein Interaction Kalpana Raja, Suresh Subramani, Jeyakumar Natarajan Data Mining and Text Mining Laboratory, Department of Bioinformatics, Bharathiar

More information

JustClust User Manual

JustClust 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 information

CPAS Overview. Josh Eckels LabKey Software jeckels@labkey.com

CPAS Overview. Josh Eckels LabKey Software jeckels@labkey.com CPAS Overview Josh Eckels LabKey Software jeckels@labkey.com CPAS Web-based system for processing, storing, and analyzing results of MS/MS experiments Key goals: Provide a great analysis front-end for

More information

Dr Alexander Henzing

Dr 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 information

Data Integration. Lectures 16 & 17. ECS289A, WQ03, Filkov

Data Integration. Lectures 16 & 17. ECS289A, WQ03, Filkov Data Integration Lectures 16 & 17 Lectures Outline Goals for Data Integration Homogeneous data integration time series data (Filkov et al. 2002) Heterogeneous data integration microarray + sequence microarray

More information

La Protéomique : Etat de l art et perspectives

La Protéomique : Etat de l art et perspectives La Protéomique : Etat de l art et perspectives Odile Schiltz Institut de Pharmacologie et de Biologie Structurale CNRS, Université de Toulouse, Odile.Schiltz@ipbs.fr Protéomique et Spectrométrie de Masse

More information

Quantitative proteomics background

Quantitative proteomics background Proteomics data analysis seminar Quantitative proteomics and transcriptomics of anaerobic and aerobic yeast cultures reveals post transcriptional regulation of key cellular processes de Groot, M., Daran

More information

AGILENT S BIOINFORMATICS ANALYSIS SOFTWARE

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 information

org.rn.eg.db December 16, 2015 org.rn.egaccnum is an R object that contains mappings between Entrez Gene identifiers and GenBank accession numbers.

org.rn.eg.db December 16, 2015 org.rn.egaccnum is an R object that contains mappings between Entrez Gene identifiers and GenBank accession numbers. org.rn.eg.db December 16, 2015 org.rn.egaccnum Map Entrez Gene identifiers to GenBank Accession Numbers org.rn.egaccnum is an R object that contains mappings between Entrez Gene identifiers and GenBank

More information

Search and Data Mining: Techniques. Applications Anya Yarygina Boris Novikov

Search and Data Mining: Techniques. Applications Anya Yarygina Boris Novikov Search and Data Mining: Techniques Applications Anya Yarygina Boris Novikov Introduction Data mining applications Data mining system products and research prototypes Additional themes on data mining Social

More information

Vad är bioinformatik och varför behöver vi det i vården? a bioinformatician's perspectives

Vad är bioinformatik och varför behöver vi det i vården? a bioinformatician's perspectives Vad är bioinformatik och varför behöver vi det i vården? a bioinformatician's perspectives Dirk.Repsilber@oru.se 2015-05-21 Functional Bioinformatics, Örebro University Vad är bioinformatik och varför

More information

University 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 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 information

Analysis of the colorectal tumor microenvironment using integrative bioinformatic tools

Analysis of the colorectal tumor microenvironment using integrative bioinformatic tools MLECNIK Bernhard & BINDEA Gabriela Analysis of the colorectal tumor microenvironment using integrative bioinformatic tools INSERM U872, Jérôme Galon Team15: Integrative Cancer Immunology Cordeliers Research

More information

RETRIEVING SEQUENCE INFORMATION. Nucleotide sequence databases. Database search. Sequence alignment and comparison

RETRIEVING SEQUENCE INFORMATION. Nucleotide sequence databases. Database search. Sequence alignment and comparison RETRIEVING SEQUENCE INFORMATION Nucleotide sequence databases Database search Sequence alignment and comparison Biological sequence databases Originally just a storage place for sequences. Currently the

More information

BBSRC TECHNOLOGY STRATEGY: TECHNOLOGIES NEEDED BY RESEARCH KNOWLEDGE PROVIDERS

BBSRC 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 information

Using Graph Theory to Analyze Gene Network Coherence

Using Graph Theory to Analyze Gene Network Coherence Using Graph Theory to Analyze Gene Network Coherence Francisco A. Gómez-Vela fgomez@upo.es Norberto Díaz-Díaz ndiaz@upo.es José A. Lagares José A. Sánchez Jesús S. Aguilar 1 Outlines Introduction Proposed

More information

Life as a scientific database curator

Life as a scientific database curator Life as a scientific database curator Sandra Orchard EBI is an Outstation of the European Molecular Biology Laboratory. What is a database curator Curator OED - a keeper of a museum or other collection

More information

Systems Biology of Cancer: which pathways to choose? Emmanuel Barillot

Systems Biology of Cancer: which pathways to choose? Emmanuel Barillot Systems Biology of Cancer: which pathways to choose? Emmanuel Barillot Central questions to cancer On the clinical side: predict the phenotype On the biological side: explain tumorigenesis and tumoral

More information

Tutorial for Proteomics Data Submission. Katalin F. Medzihradszky Robert J. Chalkley UCSF

Tutorial for Proteomics Data Submission. Katalin F. Medzihradszky Robert J. Chalkley UCSF Tutorial for Proteomics Data Submission Katalin F. Medzihradszky Robert J. Chalkley UCSF Why Have Guidelines? Large-scale proteomics studies create huge amounts of data. It is impossible/impractical to

More information

BIOINFORMATICS Supporting competencies for the pharma industry

BIOINFORMATICS 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 information

PeptidomicsDB: a new platform for sharing MS/MS data.

PeptidomicsDB: a new platform for sharing MS/MS data. PeptidomicsDB: a new platform for sharing MS/MS data. Federica Viti, Ivan Merelli, Dario Di Silvestre, Pietro Brunetti, Luciano Milanesi, Pierluigi Mauri NETTAB2010 Napoli, 01/12/2010 Mass Spectrometry

More information

GeneProf and the new GeneProf Web Services

GeneProf and the new GeneProf Web Services GeneProf and the new GeneProf Web Services Florian Halbritter florian.halbritter@ed.ac.uk Stem Cell Bioinformatics Group (Simon R. Tomlinson) simon.tomlinson@ed.ac.uk December 10, 2012 Florian Halbritter

More information

ProSightPC 3.0 Quick Start Guide

ProSightPC 3.0 Quick Start Guide ProSightPC 3.0 Quick Start Guide The Thermo ProSightPC 3.0 application is the only proteomics software suite that effectively supports high-mass-accuracy MS/MS experiments performed on LTQ FT and LTQ Orbitrap

More information

Mass Frontier 7.0 Quick Start Guide

Mass Frontier 7.0 Quick Start Guide Mass Frontier 7.0 Quick Start Guide The topics in this guide briefly step you through key features of the Mass Frontier application. Editing a Structure Working with Spectral Trees Building a Library Predicting

More information

Global and Discovery Proteomics Lecture Agenda

Global and Discovery Proteomics Lecture Agenda Global and Discovery Proteomics Christine A. Jelinek, Ph.D. Johns Hopkins University School of Medicine Department of Pharmacology and Molecular Sciences Middle Atlantic Mass Spectrometry Laboratory Global

More information

Analysis of ChIP-seq data in Galaxy

Analysis of ChIP-seq data in Galaxy Analysis of ChIP-seq data in Galaxy November, 2012 Local copy: https://galaxy.wi.mit.edu/ Joint project between BaRC and IT Main site: http://main.g2.bx.psu.edu/ 1 Font Conventions Bold and blue refers

More information

Graph-theoretical approaches for studying biological networks by. Tijana Milenković

Graph-theoretical approaches for studying biological networks by. Tijana Milenković Graph-theoretical approaches for studying biological networks by Tijana Milenković Advancement Committee: Prof. Wayne Hayes Prof. Lan Huang Prof. Eric Mjolsness Prof. Zoran Nenadić Prof. Nataša Pržulj,

More information

DeCyder Extended Data Analysis module Version 1.0

DeCyder Extended Data Analysis module Version 1.0 GE Healthcare DeCyder Extended Data Analysis module Version 1.0 Module for DeCyder 2D version 6.5 User Manual Contents 1 Introduction 1.1 Introduction... 7 1.2 The DeCyder EDA User Manual... 9 1.3 Getting

More information

UGENE Quick Start Guide

UGENE Quick Start Guide Quick Start Guide This document contains a quick introduction to UGENE. For more detailed information, you can find the UGENE User Manual and other special manuals in project website: http://ugene.unipro.ru.

More information

> Semantic Web Use Cases and Case Studies

> 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 information

Doctor of Philosophy in Computer Science

Doctor of Philosophy in Computer Science Doctor of Philosophy in Computer Science Background/Rationale The program aims to develop computer scientists who are armed with methods, tools and techniques from both theoretical and systems aspects

More information

GenBank, Entrez, & FASTA

GenBank, Entrez, & FASTA GenBank, Entrez, & FASTA Nucleotide Sequence Databases First generation GenBank is a representative example started as sort of a museum to preserve knowledge of a sequence from first discovery great repositories,

More information

Systems Biology through Data Analysis and Simulation

Systems Biology through Data Analysis and Simulation Biomolecular Networks Initiative Systems Biology through Data Analysis and Simulation William Cannon Computational Biosciences 5/30/03 Cellular Dynamics Microbial Cell Dynamics Data Mining Nitrate NARX

More information

A Graph-Theoretic Analysis of the Human Protein-Interaction Network Using Multicore Parallel Algorithms

A Graph-Theoretic Analysis of the Human Protein-Interaction Network Using Multicore Parallel Algorithms A Graph-Theoretic Analysis of the Human Protein-Interaction Network Using Multicore Parallel Algorithms David A. Bader and Kamesh Madduri College of Computing Georgia Institute of Technology, Atlanta,

More information

Extraction and Visualization of Protein-Protein Interactions from PubMed

Extraction and Visualization of Protein-Protein Interactions from PubMed Extraction and Visualization of Protein-Protein Interactions from PubMed Ulf Leser Knowledge Management in Bioinformatics Humboldt-Universität Berlin Finding Relevant Knowledge Find information about Much

More information

Biochemistry Major Talk 2014-15. Welcome!!!!!!!!!!!!!!

Biochemistry Major Talk 2014-15. Welcome!!!!!!!!!!!!!! Biochemistry Major Talk 2014-15 August 14, 2015 Department of Biochemistry The University of Hong Kong Welcome!!!!!!!!!!!!!! Introduction to Biochemistry A four-minute video: http://www.youtube.com/watch?v=tpbamzq_pue&l

More information

Network Analysis and System Biology with Omics Data. Zhenqiu Liu Samuel Oschin Comprehensive Cancer Institute Cedars Sinai Medical Center

Network Analysis and System Biology with Omics Data. Zhenqiu Liu Samuel Oschin Comprehensive Cancer Institute Cedars Sinai Medical Center Network Analysis and System Biology with Omics Data Zhenqiu Liu Samuel Oschin Comprehensive Cancer Institute Cedars Sinai Medical Center Outline System biology: core concepts and basic ideas Networks:

More information

Data, Measurements, Features

Data, Measurements, Features Data, Measurements, Features Middle East Technical University Dep. of Computer Engineering 2009 compiled by V. Atalay What do you think of when someone says Data? We might abstract the idea that data are

More information

Pipeline Pilot Enterprise Server. Flexible Integration of Disparate Data and Applications. Capture and Deployment of Best Practices

Pipeline Pilot Enterprise Server. Flexible Integration of Disparate Data and Applications. Capture and Deployment of Best Practices overview Pipeline Pilot Enterprise Server Pipeline Pilot Enterprise Server (PPES) is a powerful client-server platform that streamlines the integration and analysis of the vast quantities of data flooding

More information

E-SCIENCE IN WESTERN FRANCE :

E-SCIENCE IN WESTERN FRANCE : E-SCIENCE IN WESTERN FRANCE : BEGINS Yvan Le Bras Cyril Monjeaud Olivier Collin & the GenOuest team CNRS UMR 6074 IRISA-INRIA Context Now : Genomics : Next Generation Sequencing Now : Proteomics Next :

More information

Guidelines for Establishment of Contract Areas Computer Science Department

Guidelines for Establishment of Contract Areas Computer Science Department Guidelines for Establishment of Contract Areas Computer Science Department Current 07/01/07 Statement: The Contract Area is designed to allow a student, in cooperation with a member of the Computer Science

More information

CellNOpt: a brief overview

CellNOpt: a brief overview CellNOpt: a brief overview Thomas Cokelaer Aidan MacNamara Julio Saez-Rodriguez European Bioinformatics Institute Hinxton (Cambridge) U.K www.ebi.ac.uk/saezrodriguez Lausanne, Switzerland, April 2014 Outline

More information

Employing Power Graph Analysis to Facilitate Modeling Molecular Interaction Networks

Employing Power Graph Analysis to Facilitate Modeling Molecular Interaction Networks Employing Power Graph Analysis to Facilitate Modeling Molecular Interaction Networks Momchil Nenov 1, Svetoslav Nikolov 1,2* 1 Department of Biomechanics Institute of Mechanics Bulgarian Academy of Sciences

More information

InSyBio BioNets: Utmost efficiency in gene expression data and biological networks analysis

InSyBio 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 information

Big Data Problem? or Big Problem with Data? William Hayes, PhD SVP PlaCorm Dev, Selventa

Big Data Problem? or Big Problem with Data? William Hayes, PhD SVP PlaCorm Dev, Selventa Big Data Problem? or Big Problem with Data? William Hayes, PhD SVP PlaCorm Dev, Selventa 2013, Selventa. All Rights Reserved. Confiden;al 1 Who am I? ex- Aerospace Engineer Defected to Bioinforma;cs (PhD

More information

Work Package 13.5: Authors: Paul Flicek and Ilkka Lappalainen. 1. Introduction

Work Package 13.5: Authors: Paul Flicek and Ilkka Lappalainen. 1. Introduction Work Package 13.5: Report summarising the technical feasibility of the European Genotype Archive to collect, store, and use genotype data stored in European biobanks in a manner that complies with all

More information

Genetomic Promototypes

Genetomic Promototypes Genetomic Promototypes Mirkó Palla and Dana Pe er Department of Mechanical Engineering Clarkson University Potsdam, New York and Department of Genetics Harvard Medical School 77 Avenue Louis Pasteur Boston,

More information

A Multiple DNA Sequence Translation Tool Incorporating Web Robot and Intelligent Recommendation Techniques

A Multiple DNA Sequence Translation Tool Incorporating Web Robot and Intelligent Recommendation Techniques Proceedings of the 2007 WSEAS International Conference on Computer Engineering and Applications, Gold Coast, Australia, January 17-19, 2007 402 A Multiple DNA Sequence Translation Tool Incorporating Web

More information

Importance of Statistics in creating high dimensional data

Importance of Statistics in creating high dimensional data Importance of Statistics in creating high dimensional data Hemant K. Tiwari, PhD Section on Statistical Genetics Department of Biostatistics University of Alabama at Birmingham History of Genomic Data

More information

Euro-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 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 information

DATA MANAGEMENT PLAN IN THE REAL LIFE SCIENCES

DATA MANAGEMENT PLAN IN THE REAL LIFE SCIENCES DATA MANAGEMENT PLAN IN THE REAL LIFE SCIENCES Yvan Le Bras Cyril Monjeaud Olivier Collin Jacques Nicolas CNRS UMR 6074 IRISA-INRIA Context Now : Genomics : Next Generation Sequencing Now : Proteomics

More information

Case Study Life Sciences Data

Case Study Life Sciences Data Case Study Life Sciences Data Centre for Integrative Systems Biology and Bioinformatics www.imperial.ac.uk/bioinfsupport Sarah Butcher s.butcher@imperial.ac.uk www.imperial.ac.uk/bioinfsupport Bio-data

More information

MultiQuant Software 2.0 for Targeted Protein / Peptide Quantification

MultiQuant Software 2.0 for Targeted Protein / Peptide Quantification MultiQuant Software 2.0 for Targeted Protein / Peptide Quantification Gold Standard for Quantitative Data Processing Because of the sensitivity, selectivity, speed and throughput at which MRM assays can

More information

The EcoCyc Curation Process

The EcoCyc Curation Process The EcoCyc Curation Process Ingrid M. Keseler SRI International 1 HOW OFTEN IS THE GOLDEN GATE BRIDGE PAINTED? Many misconceptions exist about how often the Bridge is painted. Some say once every seven

More information

Prediction of Protein-Protein Interactions and Essential Genes Through Data Integration. Max Kotlyar

Prediction of Protein-Protein Interactions and Essential Genes Through Data Integration. Max Kotlyar Prediction of Protein-Protein Interactions and Essential Genes Through Data Integration by Max Kotlyar A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy Graduate

More information

泛 用 蛋 白 質 體 學 之 質 譜 儀 資 料 分 析 平 台 的 建 立 與 應 用 Universal Mass Spectrometry Data Analysis Platform for Quantitative and Qualitative Proteomics

泛 用 蛋 白 質 體 學 之 質 譜 儀 資 料 分 析 平 台 的 建 立 與 應 用 Universal Mass Spectrometry Data Analysis Platform for Quantitative and Qualitative Proteomics 泛 用 蛋 白 質 體 學 之 質 譜 儀 資 料 分 析 平 台 的 建 立 與 應 用 Universal Mass Spectrometry Data Analysis Platform for Quantitative and Qualitative Proteomics 2014 Training Course Wei-Hung Chang ( 張 瑋 宏 ) ABRC, Academia

More information

Medical Informatics II

Medical Informatics II Medical Informatics II Zlatko Trajanoski Institute for Genomics and Bioinformatics Graz University of Technology http://genome.tugraz.at zlatko.trajanoski@tugraz.at Medical Informatics II Introduction

More information

In developmental genomic regulatory interactions among genes, encoding transcription factors

In developmental genomic regulatory interactions among genes, encoding transcription factors JOURNAL OF COMPUTATIONAL BIOLOGY Volume 20, Number 6, 2013 # Mary Ann Liebert, Inc. Pp. 419 423 DOI: 10.1089/cmb.2012.0297 Research Articles A New Software Package for Predictive Gene Regulatory Network

More information

A demonstration of the use of Datagrid testbed and services for the biomedical community

A demonstration of the use of Datagrid testbed and services for the biomedical community A demonstration of the use of Datagrid testbed and services for the biomedical community Biomedical applications work package V. Breton, Y Legré (CNRS/IN2P3) R. Météry (CS) Credits : C. Blanchet, T. Contamine,

More information

Software reviews. Expression Pro ler: A suite of web-based tools for the analysis of microarray gene expression data

Software 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 information

Creating Metabolic Network Models using Text Mining and Expert Knowledge

Creating Metabolic Network Models using Text Mining and Expert Knowledge Creating Metabolic Network Models using Text Mining and Expert Knowledge J.A. Dickerson 1, D. Berleant 1, Z. Cox 1, W. Qi 1, and E. Wurtele 2 Iowa State University, Ames, IA, 50011 Abstract: This paper

More information

Big Data in Drug Discovery

Big Data in Drug Discovery Big Data in Drug Discovery David J. Wild Assistant Professor & Director, Cheminformatics Program Indiana University School of Informatics and Computing djwild@indiana.edu - http://djwild.info Epochs in

More information

1. Introduction Gene regulation Genomics and genome analyses Hidden markov model (HMM)

1. Introduction Gene regulation Genomics and genome analyses Hidden markov model (HMM) 1. Introduction Gene regulation Genomics and genome analyses Hidden markov model (HMM) 2. Gene regulation tools and methods Regulatory sequences and motif discovery TF binding sites, microrna target prediction

More information

QUALITY AND SAFETY TESTING

QUALITY AND SAFETY TESTING QUALITY AND SAFETY TESTING Large scale of solutions for the identification and rapid detection of micro-organisms. Easier investment in molecular techniques Frédéric BAR, Key Account Manager b2 b3b4 Quality

More information

Core Bioinformatics. Degree Type Year Semester. 4313473 Bioinformàtica/Bioinformatics OB 0 1

Core Bioinformatics. Degree Type Year Semester. 4313473 Bioinformàtica/Bioinformatics OB 0 1 Core Bioinformatics 2014/2015 Code: 42397 ECTS Credits: 12 Degree Type Year Semester 4313473 Bioinformàtica/Bioinformatics OB 0 1 Contact Name: Sònia Casillas Viladerrams Email: Sonia.Casillas@uab.cat

More information

An Introduction to Genomics and SAS Scientific Discovery Solutions

An Introduction to Genomics and SAS Scientific Discovery Solutions An Introduction to Genomics and SAS Scientific Discovery Solutions Dr Karen M Miller Product Manager Bioinformatics SAS EMEA 16.06.03 Copyright 2003, SAS Institute Inc. All rights reserved. 1 Overview!

More information

Basic Analysis of Microarray Data

Basic Analysis of Microarray Data Basic Analysis of Microarray Data A User Guide and Tutorial Scott A. Ness, Ph.D. Co-Director, Keck-UNM Genomics Resource and Dept. of Molecular Genetics and Microbiology University of New Mexico HSC Tel.

More information

Department of Biology Sample

Department of Biology Sample Syllabus BIOTECHNOLOGY Spring 2013 Instructor: Atanu Duttaroy, Professor Tel: 202-806-5362 Email: aduttaroy@howard.edu Office: Room 336, Just Hall Teaching Assistant: Mr. Subhas Mukherjee Lecture: Room

More information

A 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. 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 information

Software Description Technology

Software 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 information

Cloud Computing Solutions for Genomics Across Geographic, Institutional and Economic Barriers

Cloud Computing Solutions for Genomics Across Geographic, Institutional and Economic Barriers Cloud Computing Solutions for Genomics Across Geographic, Institutional and Economic Barriers Ntinos Krampis Asst. Professor J. Craig Venter Institute kkrampis@jcvi.org http://www.jcvi.org/cms/about/bios/kkrampis/

More information

The Scheduled MRM Algorithm Enables Intelligent Use of Retention Time During Multiple Reaction Monitoring

The Scheduled MRM Algorithm Enables Intelligent Use of Retention Time During Multiple Reaction Monitoring The Scheduled MRM Algorithm Enables Intelligent Use of Retention Time During Multiple Reaction Monitoring Delivering up to 2500 MRM Transitions per LC Run Christie Hunter 1, Brigitte Simons 2 1 AB SCIEX,

More information

10/4/2012. Analysis and Visualization of Biological Networks with Cytoscape. Outline of the Day. Introductions

10/4/2012. Analysis and Visualization of Biological Networks with Cytoscape. Outline of the Day. Introductions Analysis and Visualization of Biological Networks with Cytoscape John Scooter Morris, Ph.D., UCSF October 4, 2012 1 Outline of the Day Introductions and setup (15 minutes) Biological Networks (60 minutes)

More information

Proteomics Standard Group

Proteomics Standard Group Proteomics Standard Group Bioinformatique et protéomique Montbonnot 1er juin 2006 yves.vandenbrouck@cea.fr 1 Proteomics : the state of play The volume of generated proteome data is rapidly increasing Movement

More information

Virtual research environments: learning gained from a situation and needs analysis for malaria researchers

Virtual research environments: learning gained from a situation and needs analysis for malaria researchers Virtual research environments: learning gained from a situation and needs analysis for malaria researchers Martie van Deventer (CSIR), Heila Pienaar (UP), Jane Morris (ACGT) and Zoleka Ngcete (SAMI) African

More information

Eoulsan Analyse du séquençage à haut débit dans le cloud et sur la grille

Eoulsan Analyse du séquençage à haut débit dans le cloud et sur la grille Eoulsan Analyse du séquençage à haut débit dans le cloud et sur la grille Journées SUCCES Stéphane Le Crom (UPMC IBENS) stephane.le_crom@upmc.fr Paris November 2013 The Sanger DNA sequencing method Sequencing

More information

A Primer of Genome Science THIRD

A 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 information

#jenkinsconf. Jenkins as a Scientific Data and Image Processing Platform. Jenkins User Conference Boston #jenkinsconf

#jenkinsconf. Jenkins as a Scientific Data and Image Processing Platform. Jenkins User Conference Boston #jenkinsconf Jenkins as a Scientific Data and Image Processing Platform Ioannis K. Moutsatsos, Ph.D., M.SE. Novartis Institutes for Biomedical Research www.novartis.com June 18, 2014 #jenkinsconf Life Sciences are

More information

Using Ontologies in Proteus for Modeling Data Mining Analysis of Proteomics Experiments

Using Ontologies in Proteus for Modeling Data Mining Analysis of Proteomics Experiments Using Ontologies in Proteus for Modeling Data Mining Analysis of Proteomics Experiments Mario Cannataro, Pietro Hiram Guzzi, Tommaso Mazza, and Pierangelo Veltri University Magna Græcia of Catanzaro, 88100

More information

Plant Metabolomics. For BOT 6516

Plant Metabolomics. For BOT 6516 Plant Metabolomics For BOT 6516 Introduction Modern metabolomics began about ten years ago and yet many continue to question the relative performance of this area of technology in advancing plant biology.

More information

Clinical and research data integration: the i2b2 FSM experience

Clinical 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 information

Data Mining. SPSS Clementine 12.0. 1. Clementine Overview. Spring 2010 Instructor: Dr. Masoud Yaghini. Clementine

Data Mining. SPSS Clementine 12.0. 1. Clementine Overview. Spring 2010 Instructor: Dr. Masoud Yaghini. Clementine Data Mining SPSS 12.0 1. Overview Spring 2010 Instructor: Dr. Masoud Yaghini Introduction Types of Models Interface Projects References Outline Introduction Introduction Three of the common data mining

More information

Towards a Big Data Taxonomy. Bill Mandrick, PhD Data Tactics Version 26_August_2013

Towards a Big Data Taxonomy. Bill Mandrick, PhD Data Tactics Version 26_August_2013 Towards a Big Data Taxonomy Bill Mandrick, PhD Data Tactics Version 26_August_2013 Scientific Taxonomies Represent Types of Processes Types of Objects Physical Objects Information Artifacts Types of Characteristics

More information