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Logo Ateneo
   
Pathway Analysis
Data e luogo

May 17 and May 18, 2012.

The course will be held in TBA, Università degli Studi di Milano Bicocca.

Motivazioni e obiettivi

Many research programs often slow or stall after generating a gene list. The course covers the bioinformatics concepts and tools available for annotating and determining functional enrichment of a gene list and analyzing networks. The workshop is focused on the principles and concepts required for analyzing and conducting pathway analysis on a gene list from any organism, although focus will be on human and model Eukaryotic organisms. Specifically, we will focus on 1) getting more information about a gene list, 2) finding out how a set of genes is connected, 3) discovering what's enriched in a gene list (and using it for hypothesis generation) and 4) extending or refining a gene list. An analysis flow chart will be developed throughout the course.

Students will be required to complete the Cytoscape tutorials:

Target and audience

This workshop is geared towards biologists working with Omics data (e.g. gene expression, protein expression, molecular interactions, large-scale genetic screens and other omics data) from human and model Eukaryotic organisms who are interested in interpreting large gene lists resulting from their experiments. Concepts will be applicable to omics data from non-eukaryotic organisms, but software and demonstrations will not cover them. Prerequisite: Your own laptop computer. Minimum requirements: 1024x768 screen resolution, 1.5GHz CPU, 1GB RAM, recent versions of Windows, Mac OS X or Linux (Most computers purchased in the past 3-4 years likely meet these requirements).

 

Registration and information

The course is organized by the BIMIB Group of the Department of Informatics, Systems and Communication, in collaboration with the Department of Biotechnology and Biosciences and the the PhD Program in Translational and Molecular Medicine (DIMET) of the Università degli Studi di Milano Bicocca.

Web sites:

Please register by sending and email to joint-doctoral-course +at+ bimib.disco.unimib.it; the same address can be used to request other inquiries. There is no fee for registering.

Acknowledgments

Organized by: BIMIB DISCo and BtBs (Faculty of Mathematical, Physical and Natural Sciences) and DIMET (Faculty of Medicine).

The course has been made possible by the Regione Lombardia ASTIL program, project RetroNet, grant n. 12-4-5148000-40; U.A 053.

Modalità di svolgimento

Day 1 - Gene Lists

  • Module 1: Brief introduction to gene lists
    • Ice breaking session for participants (to promote networking)
    • Gene list analysis overview presenting a workflow of concepts and tools from gene list to pathway analysis
    • Where do gene lists come from?
    • Working with gene function information o Definition, sources (e.g. Gene Ontology) and issues (e.g. quality of annotation transfer, evidence codes, working with multi-functional genes)
    • Overview of pathway analysis
  • Laboratory: Practical aspects of working with gene lists
    • Workflow of tools and steps
    • Practical: review of Cytoscape tutorial
  • Module 2: Finding over-represented pathways in gene lists
    • Over-representation analysis (ORA)
    • Use of DAVID tool Statistics for detecting over-representation e.g. hypergeometric test, GSEA
    • Multiple testing correction: Bonferroni, Benjamini-Hochberg FDR
    • Filtering Gene Ontology e.g. using evidence codes
    • Text based enrichment analysis (Wyeth Wasserman)
  • Laboratory: Performing over-representation analysis
    • Workflow of tools and steps
    • Gene Set Enrichment Analysis (GSEA) and Enrichment Maps software tool
    • DAVID tool for over-representation analysis
    • Practical: Running gene enrichment tools on your gene list
  • Module 3: Pathway and Network Analysis
    • Overview of pathway and network analysis
    • Basic network concepts
    • Types of pathway and network information

Day 2 - Networks

  • Module 4: Network Visualization
    • Introduction to network visualization
    • Visualizing omics data on a network or pathway
  • Laboratory: Tutorials on Cytoscape
    • Workflow of tools and steps
    • Tutorial: Cytoscape and selected plugins
  • Module 5: Gene Function Prediction
    • Functional association networks and gene function prediction
    • Functional relationships, similarity space Homology based prediction Guilt-by-association
  • Laboratory
    • Workflow of tools and steps
    • Practical: Using GeneMANIA to assess gene and gene list function
  • Module 6: Cytoscape plugin development in Java
    • Overview and resources
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redazioneweb@disco.unimib.it - ultimo aggiornamento di questa pagina 02/05/2012