1 SRI International Bioinformatics Advanced PGDB Editing: Regulation GO Terms Ingrid M. Keseler Bioinformatics Research Group SRI International

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Presentation transcript:

1 SRI International Bioinformatics Advanced PGDB Editing: Regulation GO Terms Ingrid M. Keseler Bioinformatics Research Group SRI International

2 SRI International Bioinformatics Motivation: Why Regulation? For example: Genome and regulatory overview  Global perspective  Omics data Data sets for promoter prediction etc.

3 SRI International Bioinformatics Omics Viewer: Regulatory Overview

4 SRI International Bioinformatics Defining a New Transcription Unit Gene > New Operon Key elements – gene names in order  PTools will prompt you for a citation for the TU Specify promoter  Can use absolute or relative position of transcription start site  PTools will calculate the other value for you  PTools will prompt you for a citation for the TSS Specify sigma factor (if appropriate)  It may be necessary to first classify sigma factors under |Sigma-Factors|

5 SRI International Bioinformatics Adding Transcription Factor Binding Sites Click on TU name – Edit > Create Regulatory Interaction Select type of regulatory interaction Can put in a protein name, or select a defined TF Indicate whether it activates, represses or both Define relative distance from transcription start site  Draws DNA footprint from feature defined in TF Can edit TF binding sites by clicking on site name  Edit > Regulatory Interaction Editor Can add summaries and citations This builds the transcriptional regulatory network

6 SRI International Bioinformatics More Regulatory Interactions Attenuation Regulation of translation RNA-mediated Protein-mediated Small molecule-mediated Regulated protein or mRNA degradation (planned) If you have suggestions for types of regulation you would like to represent, or for improvements on what is there, please let us know. Tools for genome-scale datasets?

7 SRI International Bioinformatics Gene Ontology (GO) Terms

8 SRI International Bioinformatics Motivation: Why GO Terms? For example: Standardization of annotation  Data mining across genomes  Genome annotation by similarity (e.g. via InterPro, Pfam, TIGRFAM, COG mappings) Microarray data clustering Etc.

9 SRI International Bioinformatics A Word (Or Two) About GO Learn what you can about using GO  Surf the geneontology.org web site  Attend a GO Annotation Camp  Ask questions on the GO mailing lists Request new GO terms if appropriate  Useful for everybody  Have input when it counts  A new GO database can be incorporated into Pathway Tools; request help with setting up the process  Computational GO term assignments may be available for your genome via UniProt

10 SRI International Bioinformatics GO Classification Editor Accessible via the Protein Editor  Expand/contract, select/deselect by clicking on +/- and the actual terms  Selected items move to “Selections” section  Search feature: can search by name/substring or GO id (in the full format only, e.g. “GO: ”, not just the number) u For example, search for “arginine” yields many options u Click an option to highlight in hierarchy u Hovering over a term in the hierarchy brings up its definition in the middle panel u Must still click on entry in hierarchy to select the term for annotating the protein