The Gene Ontology knowledgebase in 2023

The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO-a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations-evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)-mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project

Skin biopsies in acute myeloid leukemia patients undergoing intensive chemotherapy are safe and effect patient management

Abstract There is paucity of data regarding the diagnostic yield and safety of skin biopsies in patients with acute myeloid leukemia (AML), though skin eruptions are common in these patients. We evaluated 216 patients treated in our hemato-oncology unit at a tertiary medical center between 2007 and 2018 and identified 35 patients who underwent 37 skin biopsies. The majority of biopsies were performed during induction treatment for AML (n = 26, 70%), whereas the remainder of biopsies were done prior to induction initiation (n = 8, 22%) or during consolidation chemotherapy (n = 3, 8%). Pathology findings were inconclusive in 13 cases (35%), while diagnostic biopsies were positive for drug eruptions (24%), leukemia cutis (16%), infections (11%), reactive processes (8%) and Sweet syndrome (5.5%). In almost half of cases (16/37) tissue cultures were performed. Of those, only a quarter (4/16) were positive. Histopathology and tissue culture results altered immediate patient care in 3 cases (8%), yet information obtained from biopsies had potential to affect long term patient care in 8 additional cases (21.6%). Although most skin biopsies were performed while patients had severe thrombocytopenia and neutropenia, only one patient had a complication due to the biopsy (fever and local bleeding). With the limitation of a retrospective analysis, our study suggests that skin biopsies in patients treated for AML are relatively safe. Although biopsy results infrequently alter immediate patient management, long term effect on patient care expand the potential diagnostic yield of skin biopsies

The Gene Ontology Knowledgebase in 2023

: The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and non-coding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains and updates the GO knowledgebase. The GO knowledgebase consists of three components: 1) the Gene Ontology - a computational knowledge structure describing functional characteristics of genes; 2) GO annotations - evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and 3) GO Causal Activity Models (GO-CAMs) - mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised and updated in response to newly published discoveries, and receives extensive QA checks, reviews and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, as well as guidance on how users can best make use of the data we provide. We conclude with future directions for the project

The Gene Ontology knowledgebase in 2023.

The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO-a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations-evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)-mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project