Results 31 to 40 of about 322,067 (257)

The Gene Ontology: enhancements for 2011 [PDF]

open access: yesNucleic Acids Research, 2011
The Gene Ontology (GO) (http://www.geneontology.org) is a community bioinformatics resource that represents gene product function through the use of structured, controlled vocabularies. The number of GO annotations of gene products has increased due to curation efforts among GO Consortium (GOC) groups, including focused literature-based annotation and ...
Chan, J.   +4 more
openaire   +7 more sources

Classifying genes to the correct Gene Ontology Slim term in Saccharomyces cerevisiae using neighbouring genes with classification learning

open access: yesBMC Genomics, 2010
Background There is increasing evidence that gene location and surrounding genes influence the functionality of genes in the eukaryotic genome. Knowing the Gene Ontology Slim terms associated with a gene gives us insight into a gene's functionality by ...
Tsatsoulis Costas, Amthauer Heather A
doaj   +1 more source

InfAcrOnt: calculating cross-ontology term similarities using information flow by a random walk

open access: yesBMC Genomics, 2018
Background Since the establishment of the first biomedical ontology Gene Ontology (GO), the number of biomedical ontology has increased dramatically. Nowadays over 300 ontologies have been built including extensively used Disease Ontology (DO) and Human ...
Liang Cheng   +6 more
doaj   +1 more source

A Gene Ontology Tutorial in Python [PDF]

open access: yes, 2016
This chapter is a tutorial on using Gene Ontology resources in the Python programming language. This entails querying the Gene Ontology graph, retrieving Gene Ontology annotations, performing gene enrichment analyses, and computing basic semantic similarity between GO terms.
Vesztrocy, AW, Dessimoz, C
openaire   +4 more sources

The Gene Ontology Annotation (GOA) Database: sharing knowledge in Uniprot with Gene Ontology [PDF]

open access: yesNucleic Acids Research, 2004
The Gene Ontology Annotation (GOA) database (http://www.ebi.ac.uk/GOA) aims to provide high-quality electronic and manual annotations to the UniProt Knowledgebase (Swiss-Prot, TrEMBL and PIR-PSD) using the standardized vocabulary of the Gene Ontology (GO).
Evelyn Camon   +9 more
openaire   +2 more sources

Multi-label literature classification based on the Gene Ontology graph

open access: yesBMC Bioinformatics, 2008
Background The Gene Ontology is a controlled vocabulary for representing knowledge related to genes and proteins in a computable form. The current effort of manually annotating proteins with the Gene Ontology is outpaced by the rate of accumulation of ...
Lu Xinghua   +3 more
doaj   +1 more source

Peripheral lysosomes recruit PLEKHG3 to focal adhesions and restrain protrusion dynamics

open access: yesFEBS Letters, EarlyView.
Proximity‐dependent labeling at the LAMTOR complex revealed the Rho GEF PLEKHG3 as a lysosome‐proximal protein directing the study toward the influence of lysosome positioning on actin dynamics and cell motility. We show that PLEKHG3 colocalizes with lysosomes at focal adhesion sites and observe that forced peripheral dispersion of lysosomes hinders ...
Rainer Ettelt   +8 more
wiley   +1 more source

Extending gene ontology with gene association networks [PDF]

open access: yesBioinformatics, 2015
Abstract Motivation: Gene ontology (GO) is a widely used resource to describe the attributes for gene products. However, automatic GO maintenance remains to be difficult because of the complex logical reasoning and the need of biological knowledge that are not explicitly represented in the GO.
Jiajie Peng   +4 more
openaire   +3 more sources

Defining functional distances over Gene Ontology

open access: yesBMC Bioinformatics, 2008
Background A fundamental problem when trying to define the functional relationships between proteins is the difficulty in quantifying functional similarities, even when well-structured ontologies exist regarding the activity of proteins (i.e.
del Pozo Angela   +2 more
doaj   +1 more source

Ligand‐dependent transcriptional heterogeneity in cell cycle gene expression delays G1/S entry

open access: yesFEBS Letters, EarlyView.
EGF and HRG induce distinct G1/S progression programs in ErbB2‐amplified BT474 breast cancer cells. Despite activating the potent ErbB2–ErbB3 heterodimer, HRG does not accelerate cell‐cycle entry. Instead, EGF promotes earlier restriction‐point passage via ERK–FOS signaling, whereas HRG activates the AKT–MYC axis, driving transcriptional heterogeneity ...
Ririn Rahmala Febri   +5 more
wiley   +1 more source

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