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

Usefulness of Combining NT-proBNP Level and Right Atrial Diameter for Simple and Early Noninvasive Detection of Pulmonary Hypertension Among Adult Patients with Atrial Septal Defect

Background: Atrial septal defect developed pulmonary hypertension (ASD-PH) at first diagnosis due to late presentation are common in Indonesia. Transthoracic echocardiogram (TTE) is a common tool to detect ASD-PH, before proceeding to invasive procedure. The NT-proBNP measurement to screen ASD-PH is not yet considered the standard approach, especially in limited resource conditions. The objective of this study is to assess the value of NT-proBNP, along with simple TTE parameter, to screen PH among adults with ASD. Methods: This was a cross-sectional study. The subjects were adult ASD-PH patients from the COHARD-PH registry (n=357). Right heart catheterization (RHC) was performed to diagnose PH. Blood sample was withdrawn during RHC for NT-proBNP measurement. The TTE was performed as standard procedure and its regular parameters were assessed, along with NT-proBNP, to detect PH. Results: Two parameters significantly predicted PH, namely NT-proBNP and right atrial (RA) diameter. The cut-off of NT-proBNP to detect PH was ≥140 pg/mL. The cut-off of RA diameter to detect PH was ≥46.0 mm. The combined values of NT-proBNP level ≥140 pg/mL and RA diameter ≥46.0 mm yielded 46.6 sensitivity, 91.8 specificity, 54.3 accuracy, 96.5 positive predictive value and 26.2 negative predictive value to detect PH, which were better than single value. Conclusion: NT-proBNP level ≥140 pg/mL represented PH in adult ASD patients. The NT-proBNP level ≥140 pg/mL and RA diameter ≥46.0 mm had a pre-test probability measures to triage patients needing more invasive procedure and also to determine when and if to start the PH-specific treatment. © 2022, Indonesian Society of Internal Medicine. All rights reserved

Usefulness of Combining NT-proBNP Level and Right Atrial Diameter for Simple and Early Noninvasive Detection of Pulmonary Hypertension Among Adult Patients with Atrial Septal Defect

Background: Atrial septal defect developed pulmonary hypertension (ASD-PH) at first diagnosis due to late presentation are common in Indonesia. Transthoracic echocardiogram (TTE) is a common tool to detect ASD-PH, before proceeding to invasive procedure. The NT-proBNP measurement to screen ASD-PH is not yet considered the standard approach, especially in limited resource conditions. The objective of this study is to assess the value of NT-proBNP, along with simple TTE parameter, to screen PH among adults with ASD. Methods: This was a cross-sectional study. The subjects were adult ASD-PH patients from the COHARD-PH  registry (n=357). Right heart catheterization (RHC) was performed to diagnose PH. Blood sample was withdrawn during RHC for NT-proBNP measurement. The TTE was performed as standard procedure and its regular parameters were assessed, along with NT-proBNP, to detect PH. Results: Two parameters significantly predicted PH, namely NT-proBNP and right atrial (RA) diameter. The cut-off of NT-proBNP to detect PH was ≥140 pg/mL. The cut-off of RA diameter to detect PH was ≥46.0 mm. The combined values of NT-proBNP level ≥140 pg/mL and RA diameter ≥46.0 mm yielded 46.6% sensitivity, 91.8% specificity, 54.3% accuracy, 96.5% positive predictive value and 26.2% negative predictive value to detect PH, which were better than single value. Conclusion: NT-proBNP level ≥140 pg/mL represented PH in adult ASD patients. The NT-proBNP level ≥140 pg/mL and RA diameter ≥46.0 mm had a pre-test probability measures to triage patients needing more invasive procedure and also to determine when and if to start the PH-specific treatment

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

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