Learn to use the Gene Ontology or GO, an excellent system designed to create a list of biologically relevant and carefully structured terms that can be shared among all sorts of bioinformatics resources. The controlled vocabulary terms describe gene product characteristics such as biological process, molecular function and cellular component. GO can be browsed or queried in several ways using the AmiGO browser on the GO site, and users can examine text-based displays of the hierarchies of terms or view graphical displays of the term organization, and more. Many genome databases use GO to add important functional annotations to their characterized genes.

You will learn:

  • to understand the organization of the Gene Ontology hierarchies
  • to search the AmiGO browser for terms, definitions, and annotated genes and gene products
  • to begin with sequence data and find useful terms and definitions that may help to characterize your sequence of interest
TUTORIAL RELATED CONTENT

TUTORIALS

This tutorial is a part of the tutorial group Text-related tools. You might find the other tutorials in the group interesting:

PubMatrix: PubMatrix, an on-line tool for multiplex literature mining of the PubMed database.

iHOP: Information Hyperlinked Over Proteins text mining resource

STRING: known and predicted protein-protein interactions

Textpresso: Text-mining the biological literature

XplorMed: eXploring Medline abstracts

GoMiner: Ascribe biological significance to large lists of genes by annotating them with their corresponding GO categories

Controlled Vocabularies: Standardized term lists that can enhance interactions with biological databases

DAVID: A tool that analyzes large lists of genes to provide biological meaning

Entrez Overview: Overview of NCBI's Entrez Search Resource

PubMed: PubMed access to biomedical research literature

CATEGORIES

Literature and Text Mining : Tools which are related to scientific literature. Repositories, query tools, and mining resources are included.

BLOG POSTS

Video Tip of the Week: Introduction to Biocuration and the career path: The ISB is a professional organization for biocurators At OpenHelix, we've long sung the praises of curators. Some of us have beenĀ curators and worked with curation and database development teams. All...

Video Tip of the Week: Human Phenotype Ontology, HPO: Typically, our Tips-of-the-Week cover a specific software tool or feature that we think readers would maybe like to try out. But this week's tip is a bit different. It's got a conceptual piece that is ...

Video Tip of the Week: TargetMine, Data Warehouse for Drug Discovery: Browsing around genomic regions, layering on lots of associated data, and beginning to explore new data types I might come across are things that really fire up my brain. For me, visualization is key t...

Bioinformatics tools extracted from a typical mammalian genome project [supplement]: This is Table 1 that accompanies the full blog post: Bioinformatics tools extracted from a typical mammalian genome project. See the main post for the details and explanation. The table is too long to ...

Bioinformatics tools extracted from a typical mammalian genome project: In this extended blog post, I describe my efforts to extract the information about bioinformatics-related items from a recent genome sequencing paper, and the larger issues this raises in the field. It...

BIOMED CENTRAL

Recent BioMed Central research articles citing this resource

Jin Sora et al., Identification of target genes for spermatogenic cell-specific KRAB transcription factor ZFP819 in a male germ cell line. Cell Bioscience (2017) doi:10.1186/s13578-016-0132-4

Zhu Qianglong et al., Comparative transcriptome analysis of two contrasting watermelon genotypes during fruit development and ripening Transcriptomic methods. BMC Genomics (2017) doi:10.1186/s12864-016-3442-3

Caragata P. E. et al., The transcriptome of the mosquito Aedes fluviatilis (Diptera: Culicidae), and transcriptional changes associated with its native Wolbachia infection Multicellular invertebrate genomics. BMC Genomics (2017) doi:10.1186/s12864-016-3441-4

Radovic Milos et al., Minimum redundancy maximum relevance feature selection approach for temporal gene expression data Comparative genomics. BMC Bioinformatics (2017) doi:10.1186/s12859-016-1423-9

Liu Qing et al., Identification of host proteins interacting with Toxoplasma gondii GRA15 (TgGRA15) by yeast two-hybrid system. Parasites Vectors (2017) doi:10.1186/s13071-016-1943-1