Computer Science Ph. D. Seminar Gene Ontology (GO) Based Search for Protein Structure Similarity Clustering Metrics Ph.D. Candidate Steve Johnson Committee Members Dr. Debasis Mitra, Dr. Philip Bernhard, Dr. Walter Bond, Dr. Julia Grimwade Date: September 12, 2011

Gene Ontology (GO) Based Search for Protein Structure Similarity Clustering Metrics GO Background GO Subontologies GO Annotations GO Relationships GO Tools GO Research Research Direction

Gene Ontology Background The Gene Ontology (GO), provides a consistent vocabulary for describing the attributes of proteins, specifically molecular function, biological process and the cellular component where the protein is found.

Gene Ontology Background GO Consortium Berkley Bioinformatics Open Source Project (BBOP) British Heart Foundation EcoliWiki Flybase GeneDB UniProtKB-GOA Univ. of Maryland – IGS Mouse Genome Informatics (MGI) Rat Genome Database (RGD) Saccharomyces Genome Database (SGD) The Arabidopsis Information Resource (TAIR) WormBase

Gene Ontology Background GO Consortium GO terms o A set of integer IDs (i.e., GO terms) is assigned to members of the GO Consortium GO Consortium members o provide annotations o attend all meetings, o receive funding for supported databases

Gene Ontology Project Facts Started in 1998 Primary Goals o Structured Vocabulary o Use to annotate genes and gene products 3 Model Organisms o FlyBase (Drosophila) o Saccharomyces Genome Database (SGD) o Mouse Genome Informatics (MGI) project

Gene Subontologies Three Ontology Structure Biological Process Molecular Function Cellular component

Gene Subontologies Biological Process Biological process refers to the series of steps or sequence of molecular functions. Examples of biological processes include the following. Metabolic Process Photosynthetic Process Biosynthetic Process

Gene Subontologies Molecular Function Molecular Function refers to describing the purpose of the gene product and refers to a single function (i.e., unlike biological process). Examples of molecular function include the following. Binding Activity Transport Activity Receptor Activity

Gene Subontologies Cellular Component Cellular component refer to identifying the location of the gene product within the structure of the cell. Examples of cellular components include the following. Organelle Part Cell Body Membrane Apical Complex

Example Term: Glucose Biosynthetic Process ID: GO: Definition: The formation of glucose from noncarbohydrate precursors, such as pyruvate, amino acids and glycerol. GO Annotations GO Annotation Terms

Molecular Function 8637 terms Biological Process 17,069 terms Cellular Component 2432 terms Total 28, 138 terms GO Annotations GO Annotation Term Statistics As of September 2009

GO Annotations GO Annotation Methods Electronic Annotation Manual Annotation All annotations o Source o Supportive evidence

Manual Annotation Primary source is published literature Curators perform sequence similarity analyses to transfer annotations between highly similar gene products (BLAST, protein domain analysis) GO Annotations GO Annotation Methods

Electronic Annotation Database entries o Manual mapping of GO terms to concepts external to GO (‘translation tables’) o Proteins then electronically annotated with the relevant GO term(s) Automatic sequence similarity analyses to transfer annotations between highly similar gene products GO Annotations GO Annotation Methods

1A71 Liver Alcohol Dehydrogenase GO Annotations GO Annotation Example Cellular component: Mitochondria GO: Biological Process: Ethanol Catabolic Process GO: Molecular Function: Oxireductase Activity

GO Annotations Sample Annotations GO Consortium members provide gene annotation data based on information obtained from research quality articles. The information extracted from the articles are described as “Annotation Sets” Sample Annotation Sets

GO Annotations File Format The Gene Ontology website represents the annotation data in graphical format. It is part of the Open Biomedical Ontologies (OBO), Current Species/Database Annotations Annotation File Format (GAF 2.0)

GO Annotations Evidence Code Categories The information in the annotation file includes evidence information which serves as a source to validate /the annotation information. Experimental Evidence Codes Computational Analysis Evidence Codes Author Statement Evidence Codes Curator Statement Evidence Codes

GO Annotations GO Slims GO Slims GO Slims are subsets of GO annotation information that provide broader classification of terms. GO Slim Application Example

GO Relationships A graph structure is used to establish relationship amongst the terms for molecular function, biological process, and cellular component features.graph structure Primary Ontology Relations is a part of regulates

Gene Ontology Background GO Mappings to EC Numbers Enzyme Commission numbers are used to specify categories of enzymes based on the chemical reactions catalyzed. The UniProtKB-GOA EC2GO mapping provides GO molecular function IDs for each classificationUniProtKB-GOA EC2GO EC1 - Oxidoreductases EC2 - Transferases EC3 - Hydrolases EC4 - Lyases EC5 – Isomerases EC 6 - Ligases

GO Tools Amigo OBO – Edit QuickGO Goanna agriGO

Gene Ontology Database MySQL Querying GO MySQL o SQL o Perl o GHOUL

Gene Ontology Interesting Research GO Annotation Consistency Automated Annotation Biocreative CLUGO Similarity Prediction Method Automated Protein Function Predictions Search for Genes w/ Similar Function Semantic Similarity

Dissertation Research Hypothesis There exists protein alignment metrics/algorithms that can be used as clustering indexes for proteins with matching GO molecular functions IDs

Gene Ontology References Evelyn B Camon, Daniel G Barrell, Emily C Dimmer, Vivian Lee, Michele Magrane, John Maslen, David Binns and Rolf Apweiler; An evaluations of GO annotation retrieval for BioCreAtIvE and GOA. BMC Bioinformatices (Supplement 1): S17. Mary E. Dolan, Li Ni, Evelyn Camon and Judith A. Blake; A procedure for assessing GO annotation consistency. Bioinformatics (Supplement 1): i136 – i143. In-Yee Lee, Jan-Ming Ho, Ming-Syan Chen; CLUGO: A Clustering Algorithm for Automated Functional Annotations Based on Gene Ontology. Proceedings of the 5 th IEEE International Conference on Data Mining (ICDM, 05): i136 – i143. Gene Ontology Consortium; The Gene Ontology in 2010: extensions and refinements. Nucleic Acids Research, Evelyn Camon, Michele Magrane, Daniel Barrell, Vivian Lee, Emily Dimmer, John Maslen, David Binns, Nicola Harte, Rodrigo Lopez and Rolf Apweiler; The Gene Ontology Annotation (GOA) Database: sharing knowledge in Uniprot with Gene Ontology. Nucleic Acids Research, 2004 (32).

Gene Ontology References Gene Ontology Consortium; The Gene Ontology (GO) database and informatics resource. Nucleic Acids Research, 2004 (32). Seth Carbon1, Amelia Ireland2, Christopher J. Mungall, ShengQiang Shu, Brad Marshall, Suzanna Lewis; Amigo: online access to ontology and annotation data. Bioinformatics Application Note. 22 (2), 2009: 288 – 289.