'Gene set' presentation slideshows

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Canadian Bioinformatics Workshops

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Divining Systems Biology Knowledge from High-throughput Experiments Using EGAN

Divining Systems Biology Knowledge from High-throughput Experiments Using EGAN. Jesse Paquette ISMB 2010 Biostatistics and Computational Biology Core Helen Diller Family Comprehensive Cancer Center University of California, San Francisco (AKA BCBC HDFCCC UCSF). High-throughput experiments.

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Buried treasures Old statistics in new contexts

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Mechanistic Models of Cancer Progression in the Space of Pathways

Mechanistic Models of Cancer Progression in the Space of Pathways. Elena Edelman eje2@duke.edu Computational Biology and Bioinformatics Program Institute of Genome Policy and Science Duke University. Outline. I. Biological Background Problems with single gene analysis

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Canadian Bioinformatics Workshops

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Joint analysis of regulatory networks and expression profiles

Joint analysis of regulatory networks and expression profiles. Ron Shamir School of Computer Science Tel Aviv University April 2013. Sources: Igor Ulitsky and Ron Shamir. Identification of Functional Modules using Network Topology and High-Throughput Data. BMC Systems Biology 1:8 (2007).

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Integrating Biology and Statistics: Gene Set Methods

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WormBase - and the not so stable genome.

WormBase - and the not so stable genome. Paul Davis, WormBase. Overview. Genome Overview Project. Layout. Data as of 1998. Curated Gene Set and Genome Genome stats. Gene stats. Gene curation. User Community and catering for their needs. The Genome Sequencing Project.

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Regulatory Genomics Lab

Regulatory Genomics Lab. Saurabh Sinha. Powerpoint by Casey Hanson. Exercise. In this exercise, we will do the following: . Use Galaxy to manipulate a ChIP track for BIN in D. Mel. Subject peak sets to MEME suite. Compare MEME motifs with Fly Factor Survey motifs for BIN.

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Intro to Comp Genomics

Intro to Comp Genomics. Lecture 7: Using large scale functional genomics datasets. Your Task. Your Task. Modeling. S. P1. Preparations: Get your hand on the ChIP-seq profiles of CTCF and PolII in hg chr17, bin-size = 50bp Cut the data into segments of 50,000 data points Modeling:

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Keith Skubitz 1 , Princy Francis 2 , Amy Skubitz 1 , Xianghua Luo 1 , and Mef Nilbert 2,3

Use of gene expression to identify heterogeneity of metastatic behavior among high-grade pleomorphic soft tissue sarcomas. Keith Skubitz 1 , Princy Francis 2 , Amy Skubitz 1 , Xianghua Luo 1 , and Mef Nilbert 2,3 1 University of Minnesota, 2 Lund University, 3 Hvidovre Hospital.

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Distinguishing Regulators of Biomolecular Pathways

Distinguishing Regulators of Biomolecular Pathways. Mentor: Dr. Xiwei Wu City of Hope. Sean Caonguyen SoCalBSI 8/21/08. Expression Pattern Analysis. Microarray technology is a powerful tool for investigating cellular activity at different levels

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UCSC Known Genes Version 3 Take 9

UCSC Known Genes Version 3 Take 9. Known Gene History. Initially based on Genie predictions constrained by BLAT mRNA alignments. David Kulp got busy at Affy. Switched to RefSeq Jim got paranoid Riken RNAs would take over Fan built KG 1 Mark got annoyed at low quality predictions

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VectorBase vectorbase

new genomes. new features. and future plans. Daniel Lawson (on behalf of VectorBase). VectorBase http://www.vectorbase.org. Kolymbari Meeting July 2011. VectorBase. University of Notre Dame. EMBL-EBI. IMBB. Harvard University. University of New Mexico. Imperial College, London.

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Assembly Validation

Assembly Validation. Gene space statistics. Is my genome assembled good enough?. CEGMA predicted Genes in genome. CEGMA core proteins. mapping. BUSCO genes in genome. HMM search. BUSCO profiles. Proteins with hit to BUSCO gene set. gmap. ESTs mapped to genome scaffolds.

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Gene Set Enrichment Analysis (GSEA)

Gene Set Enrichment Analysis (GSEA). Gene Set Enrichment. Example: human diabetes. Skeletal muscle biopsies. No single gene was found to be significantly regulated

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Exercise 5: Looking for overreprsented GO terms in a gene set using Onto-Express

Exercise 5: Looking for overreprsented GO terms in a gene set using Onto-Express. GO annotations can be used to obtain functional data about gene sets e.g. from gene expression experiments.

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AR Jex et al. Nature 000 , 1-5 (2011) doi:10.1038/nature10553

Venn diagram summarizing the overlapping homology between the Ascaris suum gene set and those of other nematodes. AR Jex et al. Nature 000 , 1-5 (2011) doi:10.1038/nature10553.

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Predicting Survival Time From Genomic Data

Predicting Survival Time From Genomic Data Maria D. Gonzalez Gil ( mgg28331@gmail.com ) , Mentor: Larry Hall. Conclusion The probabilistic ordering after the traveling salesman has an effect with larger numbers of examples. For example, there are at most 2 orderings for the NO.

116 views • 1 slides