The Gene Ontology knowledgebase in 2023

Genetics, Journal Year: 2023, Volume and Issue: 224(1)

Published: March 3, 2023

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

Language: Английский

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Annotation of biologically relevant ligands in UniProtKB using ChEBI

Bioinformatics, Journal Year: 2022, Volume and Issue: 39(1)

Published: Dec. 8, 2022

Abstract Motivation To provide high quality, computationally tractable annotation of binding sites for biologically relevant (cognate) ligands in UniProtKB using the chemical ontology ChEBI (Chemical Entities Biological Interest), to better support efforts study and predict functionally interactions between protein sequences structures small molecule ligands. Results We structured data model cognate ligand site annotations performed a complete reannotation all stable unique identifiers from ChEBI, which we now use as reference vocabulary such annotations. developed improved search query facilities UniProt website, REST API SPARQL endpoint that leverage structure data, nomenclature classification provides. Availability implementation Binding described are available sequence records several formats (text, XML RDF) freely download through website (www.uniprot.org), (www.uniprot.org/help/api), (sparql.uniprot.org/) FTP (https://ftp.uniprot.org/pub/databases/uniprot/). Supplementary information at Bioinformatics online.

Language: Английский

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WormBase 2024: status and transitioning to Alliance infrastructure

Genetics, Journal Year: 2024, Volume and Issue: 227(1)

Published: April 4, 2024

Abstract WormBase has been the major repository and knowledgebase of information about genome genetics Caenorhabditis elegans other nematodes experimental interest for over 2 decades. We have 3 goals: to keep current with fast-paced C. research, provide better integration resources, be sustainable. Here, we discuss state as well progress plans moving core infrastructure Alliance Genome Resources (the Alliance). As an member, will continue interact community, develop new features needed, curate key from literature large-scale projects.

Language: Английский

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The Arabidopsis Information Resource in 2024

Genetics, Journal Year: 2024, Volume and Issue: 227(1)

Published: March 8, 2024

Since 1999, The Arabidopsis Information Resource (www.arabidopsis.org) has been curating data about the thaliana genome. Its primary focus is integrating experimental gene function information from peer-reviewed literature and codifying it as controlled vocabulary annotations. Our goal to produce a "gold standard" functional annotation set that reflects current state of knowledge At same time, resource serves nexus for community-based collaborations aimed at improving quality, access, reuse. For past decade, our work made possible by subscriptions global user base. This update covers ongoing biocuration work, some modernization efforts contribute first major infrastructure overhaul since 2011, introduction JBrowse2, resource's role in community activities such organizing structural reannotation assessment, we used ontology annotations metric evaluate: (1) what currently known (2) "unknown" genes. Currently, 74% proteome annotated least one term. Of those loci, half have support following aspects: molecular function, biological process, or cellular component. sheds light on genes which not yet identified any published no annotation. Drawing attention these unknown highlights gaps potential sources novel discoveries.

Language: Английский

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DisProt in 2024: improving function annotation of intrinsically disordered proteins

Nucleic Acids Research, Journal Year: 2023, Volume and Issue: 52(D1), P. D434 - D441

Published: Oct. 30, 2023

Abstract DisProt (URL: https://disprot.org) is the gold standard database for intrinsically disordered proteins and regions, providing valuable information about their functions. The latest version of brings significant advancements, including a broader representation functions an enhanced curation process. These improvements aim to increase both quality annotations coverage at sequence level. Higher has been achieved by adopting additional evidence codes. Quality improved systematically applying Minimum Information About Disorder Experiments (MIADE) principles reporting all details experimental setup that could potentially influence structural state protein. now includes new thematic datasets expanded adoption Gene Ontology terms, resulting in extensive functional repertoire which automatically propagated UniProtKB. Finally, we show DisProt's curated strongly correlate with disorder predictions inferred from AlphaFold2 pLDDT (predicted Local Distance Difference Test) confidence scores. This comparison highlights utility explaining apparent uncertainty certain well-defined predicted structures, often correspond folding-upon-binding fragments. Overall, serves as comprehensive resource, combining enhance our understanding implications.

Language: Английский

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Protein function prediction as approximate semantic entailment

Nature Machine Intelligence, Journal Year: 2024, Volume and Issue: 6(2), P. 220 - 228

Published: Feb. 14, 2024

Abstract The Gene Ontology (GO) is a formal, axiomatic theory with over 100,000 axioms that describe the molecular functions, biological processes and cellular locations of proteins in three subontologies. Predicting functions using GO requires both learning reasoning capabilities order to maintain consistency exploit background knowledge GO. Many methods have been developed automatically predict protein but effectively exploiting all for knowledge-enhanced has remained challenge. We DeepGO-SE, method predicts from sequences pretrained large language model. DeepGO-SE generates multiple approximate models GO, neural network truth values statements about these models. aggregate so approximates semantic entailment when predicting functions. show, several benchmarks, approach exploits improves function prediction compared state-of-the-art methods.

Language: Английский

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Annotation of biologically relevant ligands in UniProtKB using ChEBI

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2022, Volume and Issue: unknown

Published: Aug. 22, 2022

Abstract Motivation To provide high quality, computationally tractable annotation of binding sites for biologically relevant (cognate) ligands in UniProtKB using the chemical ontology ChEBI (Chemical Entities Biological Interest), to better support efforts study and predict functionally interactions between proteins small molecule ligands. Results We structured data model cognate ligand site annotations performed a complete reannotation all stable unique identifiers from ChEBI, which we now use as reference vocabulary such annotations. developed improved search query facilities UniProt website, REST API SPARQL endpoint that leverage structure data, nomenclature, classification provides. Availability Binding described are available protein sequence records several formats (text, XML, RDF), freely download through website ( www.uniprot.org ), www.uniprot.org/help/api sparql.uniprot.org/ FTP https://ftp.uniprot.org/pub/databases/uniprot/ ). Contact [email protected] Supplementary information Table 1.

Language: Английский

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RegulonDB v12.0: a comprehensive resource of transcriptional regulation in E. coli K-12

Nucleic Acids Research, Journal Year: 2023, Volume and Issue: 52(D1), P. D255 - D264

Published: Nov. 16, 2023

RegulonDB is a database that contains the most comprehensive corpus of knowledge regulation transcription initiation Escherichia coli K-12, including data from both classical molecular biology and high-throughput methodologies. Here, we describe biological advances since our last NAR paper 2019. We explain changes to satisfy FAIR requirements. also present full reconstruction computational infrastructure, which has significantly improved storage, retrieval accessibility thus supports more intuitive user-friendly experience. The integration graphical tools provides clear visual representations genetic data, facilitating interpretation integration. version 12.0 can be accessed at https://regulondb.ccg.unam.mx.

Language: Английский

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An ontology-based rare disease common data model harmonising international registries, FHIR, and Phenopackets

Scientific Data, Journal Year: 2025, Volume and Issue: 12(1)

Published: Feb. 8, 2025

Abstract Although rare diseases (RDs) affect over 260 million individuals worldwide, low data quality and scarcity challenge effective care research. This work aims to harmonise the Common Data Set by European Rare Disease Registry Infrastructure, Health Level 7 Fast Healthcare Interoperability Base Resources, Global Alliance for Genomics Phenopacket Schema into a novel disease common model (RD-CDM), laying foundation developing international RD-CDMs aligned with these standards. We developed modular-based GitHub repository documentation account flexibility, extensions further development. Recommendations on model’s cardinalities are given, inviting refinement collaboration. An ontology-based approach was selected find denominator between semantic syntactic Our RD-CDM version 2.0.0 comprises 78 elements, extending ERDRI-CDS 62 elements previous versions implemented in four German university hospitals capturing real world development evaluation. identified three categories evaluation: Medical Granularity, Clinical Reasoning Relevance, Harmonisation.

Language: Английский

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Decoding the Molecular Language of Proteins with Evola

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 6, 2025

Abstract Proteins, nature’s intricate molecular machines, are the products of billions years evolution and play fundamental roles in sustaining life. Yet, deciphering their language - that is, understanding how protein sequences structures encode determine biological functions remains a cornerstone challenge modern biology. Here, we introduce Evola, an 80 billion frontier protein-language generative model designed to decode proteins. By integrating information from sequences, structures, user queries, Evola generates precise contextually nuanced insights into function. A key innovation lies its training on unprecedented AI-generated dataset: 546 million question-answer pairs 150 word tokens, reflect immense complexity functional diversity Post-pretraining, integrates Direct Preference Optimization (DPO) refine based preference signals Retrieval-Augmented Generation (RAG) for external knowledge incorporation, improving response quality relevance. To evaluate performance, propose novel framework, Instructional Response Space (IRS), demonstrating delivers expert-level insights, advancing research proteomics genomics while shedding light logic encoded The online demo is available at http://www.chat-protein.com/ .

Language: Английский

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