IndraLab
Statements
sparser
"We have released version 2 of a comprehensive set of integrated, reviewed annotations for human genes, which we call the “functionome.” We have also dramatically increased the number of GO-CAM models, with over 1500 models of metabolic and signaling pathways, primarily in human, mouse, budding and fission yeast, and fruit fly."
sparser
"The information: miR-4691-3p acts via its ‘ mRNA base-pairing translational repressor activity ’ (GO:1903231) as part of ‘ miRNA-mediated post-transcriptional gene silencing ’ (GO:0035195) of STING1 occurring in the ‘cytosol’ (GO:0005829) as part of ‘negative regulation of cGAS/STING signaling pathway’ (GO:0160049), as part of the ‘negative regulation of innate immune response ’ (GO:0045824) was curated from [ xref ] and integrated into a GO-CAM of the human cGAS/STING signalling pathway."
sparser
"GO-CAM, our new framework for defining and representing gene functions with more accuracy, consistency and precision, is being used to create a growing set of curated biological models, and we encourage the analysis tool developer community to explore the new format and potential new applications of these models."
sparser
"In GO-CAM, each model is represented as a set of triples ( subject - relation -object, with brackets {} as a set container), e.g. { ABCA1 enables cholesterol transporter activity ; cholesterol transporter activity occurs in plasma membrane , and cholesterol transporter activity part_of cholesterol homeostasis}."
sparser
"татье кратко представлены особенности предметной области (биоинформатика, системная биология, биомедицина), формальные определения понятия онтологии и графов знаний приведены примеры применения онтологий для семантической интеграции гетерогенных данных и создания
больших баз знаний, а также интерпретации результатов глубокого обучения на больших данных. В качестве
примера успешного проекта описана база знаний Gene Ontology, которая помимо терминологических знаний и
аннотаций генов (GOA) включает модели причинных влияний (GO-CAM)."
sparser
"In order to obtain information about
the function of a gene or its product (RNA, protein) in a particular
biological process and a particular cellular structure,
it was necessary to develop another component of the GO
knowledge base – the GO-CAM model of causal influences
between gene products (Thomas et al., 2019)"
sparser
"GO-CAM links several GO annotations together to create
models of biological processes that connect the activities of
more than one gene product together into causal networks
and allow specification of the biological context (e. g. cell/
tissue type) in which the activities occur."
sparser
"GO-CAM thus provides the opportunity to use the massive
GO and GOA knowledge base accumulated over the last
20 years as a basis not only for genomic biology representation
of gene function, but also for a broader representation of
systems biology and its novel applications to the interpretation
of large-scale experimental data"
sparser
"Thomas P.D., Hill D.P., Mi H., Osumi-Sutherland D., Van Auken K.,
Carbon S., Balhoff J.P., Albou L.-P., Good B., Gaudet P., Lewis S.E.,
Mungall C.J. Gene Ontology Causal Activity Modeling (GO-CAM)
moves beyond GO annotations to structured descriptions of biological
functions and systems."
sparser
"To adapt the GO–CAM framework for modelling neurobiological statements about C. elegans egg-laying and carbon dioxide (CO 2 )-sensing behaviors, we selected a subset of relevant papers from the C. elegans bibliography and identified author statements that could be used to support construction of semantically rigorous, causal models."
sparser
"For example, AmiGO [ xref ] and GO-CAM [ xref ] enable functional annotations of genes and gene products, GOSemSim provides an R package for measuring semantic similarity among GO terms and gene products [ xref ], PANTHER is a web service for GO enrichment analysis [ xref ], and PhenIX effectively diagnoses genetic diseases through computational phenotype analysis of disease-associated genomes [ xref ]."
sparser
"For example, high-throughput experiments for gene expression generate hundreds or sometimes thousands of differentially expressed genes (DEGs), and their associated biological functions can be summarized through enrichment analysis over GO terms. xref Gene-level annotations defined in GO can also be further elaborated into a network of biological pathway annotations via the recently developed GO Causal Activity Modeling (GO-CAM) models to represent the integrative effect of DEGs on the level of biological pathways."
sparser
"One of the curatorial goals of WormBase and the GO Consortium is to model such pathways using the GO-CAM framework in which GO molecular functions (MFs) are linked to one another with causal relations, e.g. directly positively regulates [RO:0 002 629], from the Relations Ontology [ xref ]."
sparser
"A GO-CAM differs from the Reactome model of the same process in that the latter employs a more discursive process description data model ( xref ) to describe processes as networks of reactions mediated by gene products that transform input molecules into output molecules ( xref )."
sparser
"A specific feature of GO-CAM models generated in the work described here is that each covers a group of molecular functions corresponding to a single GO biological process, while Reactome models are more variable in size and scope, combining, for example, metabolic and regulatory functions, and merging multiple tissue-specific variant forms of a process."
sparser
"The focus has been in three broad areas: improving the representation of biological functions in the GO ontology, increasing the coverage (of published function determination via experiments) and quality of gene function annotations, and increasing the number and biological scope of GO-CAM models."
sparser
"To adapt the GO-CAM framework for modelling neurobiological statements about C. elegans egg-laying and carbon dioxide (CO 2 )-sensing behaviors, we selected a subset of relevant papers from the C. elegans bibliography and identified author statements that could be used to support construction of semantically rigorous, causal models."
sparser
"Here, we have shown that human GO-CAM models of glycolysis, gluconeogenesis, and pyruvate metabolism serve as accurate templates for modeling the orthologous mouse pathways, that VLAD analysis of phenotypes associated with mutant mouse genes associated distinct but related phenotypes with mutational disruptions of genes involved in each pathway, and that analysis of common enriched phenotypes further supported the identification of transcription factors that play major roles in regulating these pathways."
sparser
"In parallel, the Gene Ontology [GO ( xref )], since 2003, has included a ‘regulation of biological process’ (GO:0050789) branch that has been widely used to annotate causal interactions ( xref ), and has recently been extended into the GO Causal Activity Models (GO-CAM) framework ( xref )."
sparser
"Current formats of causal statements range from the simplest, with only two entities and the causal relationship [e.g. the Simple Interaction Format (SIF) with ‘A activates B’ or ‘A -> B’], to more complex statements including contextual description [e.g. BEL (Biological Expression Language) ( xref ; xref ), GO-CAM ( xref ) and PSI-MITAB2.8 ( xref )]."
sparser
"Neither GO-CAM construction nor VLAD analysis was trained or optimized for these domains of biology, however, so these results are useful as a test of a general strategy for pathway annotation and analysis, and suggest that it can be extended to less exhaustively studied processes and less well characterized species."
sparser
"We focus on our progress on the curation and public release of GO-CAM models, the continuous collaborative work to refine the GO ontology, the review and improvement of the quality of our annotations, and the expansion of the usability of GO through a redesigned website, documentation, data access, visualization widget and 15 years of historical archives of the GO knowledgebase."
sparser
"Reactome annotations of human pathways of glycolysis, gluconeogenesis, and pyruvate metabolism to lactate or acetyl-CoA identified functions for 60 human gene products, 44 of which have high-confidence mouse structural orthologs (Table1), enabling the streamlined generation of mouse GO-CAM models by swapping human gene products for their mouse counterparts."
sparser
"The biggest change has been in biological process terms, due to refactoring the multi-organism part of the Biological Process branch and the obsoletion of combinatorial terms (e.g. GO:0100052, negative regulation of G1/S transition of mitotic cell cycle by transcription from RNA polymerase II promoter) made up of other GO terms which can now be linked using GO-CAM."
sparser
"The GO-CAM model for complement activation has 11 step-enabling entities but the gene list has 117 members again due to set inflation (unadjusted p-value of 0.27 for 7/117 genes in fibroblasts in the LMNA genotype in our implementation; not reported as a significant result by PANTHER for 8/120 genes; unadjusted p-value of 0.70 for 9/156 entities in the Reactome Analysis tool) [ xref , xref ]."
sparser
"Using the Gene Ontology resources and GO-CAM model of analysis, which is a combination of standard GO annotations allowing to produce a network of annotations, we were able to identify several GO biological processes, SSC-VSELs and FSH + NAM VSELs, including multicellular organism development, organogenesis, regulation of gene expression, signal transduction, Wnt signaling pathway, cytoskeleton organization, cell adhesion, negative regulation of the apoptotic process, response to extra- and intracellular stimuli, protein transport and stabilization, protein phosphorylation and ubiquitination, DNA repair, immune response, and regulation of circadian rhythm."
sparser
"In xref , Zone b (dotted line) addresses the competency question: “What biological processes or pathways are impacted by a specific disease?” Here, NAFLD is linked to various pathways, including the “fatty acid biosynthetic process” and GO-CAM models, showing TEKG’s ability to identify affected biological processes."