Database: The Journal of Biological Databases and Curation最新文献

{"title":"A change language for ontologies and knowledge graphs.","authors":"Harshad Hegde, Jennifer Vendetti, Damien Goutte-Gattat, J Harry Caufield, John B Graybeal, Nomi L Harris, Naouel Karam, Christian Kindermann, Nicolas Matentzoglu, James A Overton, Mark A Musen, Christopher J Mungall","doi":"10.1093/database/baae133","DOIUrl":"https://doi.org/10.1093/database/baae133","url":null,"abstract":"<p><p>Ontologies and knowledge graphs (KGs) are general-purpose computable representations of some domain, such as human anatomy, and are frequently a crucial part of modern information systems. Most of these structures change over time, incorporating new knowledge or information that was previously missing. Managing these changes is a challenge, both in terms of communicating changes to users and providing mechanisms to make it easier for multiple stakeholders to contribute. To fill that need, we have created KGCL, the Knowledge Graph Change Language (https://github.com/INCATools/kgcl), a standard data model for describing changes to KGs and ontologies at a high level, and an accompanying human-readable Controlled Natural Language (CNL). This language serves two purposes: a curator can use it to request desired changes, and it can also be used to describe changes that have already happened, corresponding to the concepts of \"apply patch\" and \"diff\" commonly used for managing changes in text documents and computer programs. Another key feature of KGCL is that descriptions are at a high enough level to be useful and understood by a variety of stakeholders-e.g. ontology edits can be specified by commands like \"add synonym 'arm' to 'forelimb'\" or \"move 'Parkinson disease' under 'neurodegenerative disease'.\" We have also built a suite of tools for managing ontology changes. These include an automated agent that integrates with and monitors GitHub ontology repositories and applies any requested changes and a new component in the BioPortal ontology resource that allows users to make change requests directly from within the BioPortal user interface. Overall, the KGCL data model, its CNL, and associated tooling allow for easier management and processing of changes associated with the development of ontologies and KGs. Database URL: https://github.com/INCATools/kgcl.</p>","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":"2025 ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144126968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A change language for ontologies and knowledge graphs.","authors":"Harshad Hegde, Jennifer Vendetti, Damien Goutte-Gattat, J Harry Caufield, John B Graybeal, Nomi L Harris, Naouel Karam, Christian Kindermann, Nicolas Matentzoglu, James A Overton, Mark A Musen, Christopher J Mungall","doi":"10.1093/database/baae133","DOIUrl":"10.1093/database/baae133","url":null,"abstract":"<p><p>Ontologies and knowledge graphs (KGs) are general-purpose computable representations of some domain, such as human anatomy, and are frequently a crucial part of modern information systems. Most of these structures change over time, incorporating new knowledge or information that was previously missing. Managing these changes is a challenge, both in terms of communicating changes to users and providing mechanisms to make it easier for multiple stakeholders to contribute. To fill that need, we have created KGCL, the Knowledge Graph Change Language (https://github.com/INCATools/kgcl), a standard data model for describing changes to KGs and ontologies at a high level, and an accompanying human-readable Controlled Natural Language (CNL). This language serves two purposes: a curator can use it to request desired changes, and it can also be used to describe changes that have already happened, corresponding to the concepts of \"apply patch\" and \"diff\" commonly used for managing changes in text documents and computer programs. Another key feature of KGCL is that descriptions are at a high enough level to be useful and understood by a variety of stakeholders-e.g. ontology edits can be specified by commands like \"add synonym 'arm' to 'forelimb'\" or \"move 'Parkinson disease' under 'neurodegenerative disease'.\" We have also built a suite of tools for managing ontology changes. These include an automated agent that integrates with and monitors GitHub ontology repositories and applies any requested changes and a new component in the BioPortal ontology resource that allows users to make change requests directly from within the BioPortal user interface. Overall, the KGCL data model, its CNL, and associated tooling allow for easier management and processing of changes associated with the development of ontologies and KGs. Database URL: https://github.com/INCATools/kgcl.</p>","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":"2025 ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11753292/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143022562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Standardized pipelines support and facilitate integration of diverse datasets at the Rat Genome Database.","authors":"Jennifer R Smith, Marek A Tutaj, Jyothi Thota, Logan Lamers, Adam C Gibson, Akhilanand Kundurthi, Varun Reddy Gollapally, Kent C Brodie, Stacy Zacher, Stanley J F Laulederkind, G Thomas Hayman, Shur-Jen Wang, Monika Tutaj, Mary L Kaldunski, Mahima Vedi, Wendy M Demos, Jeffrey L De Pons, Melinda R Dwinell, Anne E Kwitek","doi":"10.1093/database/baae132","DOIUrl":"10.1093/database/baae132","url":null,"abstract":"<p><p>The Rat Genome Database (RGD) is a multispecies knowledgebase which integrates genetic, multiomic, phenotypic, and disease data across 10 mammalian species. To support cross-species, multiomics studies and to enhance and expand on data manually extracted from the biomedical literature by the RGD team of expert curators, RGD imports and integrates data from multiple sources. These include major databases and a substantial number of domain-specific resources, as well as direct submissions by individual researchers. The incorporation of these diverse datatypes is handled by a growing list of automated import, export, data processing, and quality control pipelines. This article outlines the development over time of a standardized infrastructure for automated RGD pipelines with a summary of key design decisions and a focus on lessons learned.</p>","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":"2025 ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11753291/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143022144","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction to: The landscape of microRNA interaction annotation: analysis of three rare disorders as a case study.","authors":"","doi":"10.1093/database/baae131","DOIUrl":"https://doi.org/10.1093/database/baae131","url":null,"abstract":"","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":"2025 ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144126787","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction to: The landscape of microRNA interaction annotation: analysis of three rare disorders as a case study.","authors":"","doi":"10.1093/database/baae131","DOIUrl":"10.1093/database/baae131","url":null,"abstract":"","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":"2025 ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11726336/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142969881","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"LSD600: the first corpus of biomedical abstracts annotated with lifestyle-disease relations.","authors":"Esmaeil Nourani, Evangelia-Mantelena Makri, Xiqing Mao, Sampo Pyysalo, Søren Brunak, Katerina Nastou, Lars Juhl Jensen","doi":"10.1093/database/baae129","DOIUrl":"https://doi.org/10.1093/database/baae129","url":null,"abstract":"<p><p>Lifestyle factors (LSFs) are increasingly recognized as instrumental in both the development and control of diseases. Despite their importance, there is a lack of methods to extract relations between LSFs and diseases from the literature, a step necessary to consolidate the currently available knowledge into a structured form. As simple co-occurrence-based relation extraction (RE) approaches are unable to distinguish between the different types of LSF-disease relations, context-aware models such as transformers are required to extract and classify these relations into specific relation types. However, no comprehensive LSF-disease RE system existed, nor a corpus suitable for developing one. We present LSD600 (available at https://zenodo.org/records/13952449), the first corpus specifically designed for LSF-disease RE, comprising 600 abstracts with 1900 relations of eight distinct types between 5027 diseases and 6930 LSF entities. We evaluated LSD600's quality by training a RoBERTa model on the corpus, achieving an F-score of 68.5% for the multilabel RE task on the held-out test set. We further validated LSD600 by using the trained model on the two Nutrition-Disease and FoodDisease datasets, where it achieved F-scores of 70.7% and 80.7%, respectively. Building on these performance results, LSD600 and the RE system trained on it can be valuable resources to fill the existing gap in this area and pave the way for downstream applications. Database URL: https://zenodo.org/records/13952449.</p>","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":"2025 ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144126808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"LSD600: the first corpus of biomedical abstracts annotated with lifestyle-disease relations.","authors":"Esmaeil Nourani, Evangelia-Mantelena Makri, Xiqing Mao, Sampo Pyysalo, Søren Brunak, Katerina Nastou, Lars Juhl Jensen","doi":"10.1093/database/baae129","DOIUrl":"10.1093/database/baae129","url":null,"abstract":"<p><p>Lifestyle factors (LSFs) are increasingly recognized as instrumental in both the development and control of diseases. Despite their importance, there is a lack of methods to extract relations between LSFs and diseases from the literature, a step necessary to consolidate the currently available knowledge into a structured form. As simple co-occurrence-based relation extraction (RE) approaches are unable to distinguish between the different types of LSF-disease relations, context-aware models such as transformers are required to extract and classify these relations into specific relation types. However, no comprehensive LSF-disease RE system existed, nor a corpus suitable for developing one. We present LSD600 (available at https://zenodo.org/records/13952449), the first corpus specifically designed for LSF-disease RE, comprising 600 abstracts with 1900 relations of eight distinct types between 5027 diseases and 6930 LSF entities. We evaluated LSD600's quality by training a RoBERTa model on the corpus, achieving an F-score of 68.5% for the multilabel RE task on the held-out test set. We further validated LSD600 by using the trained model on the two Nutrition-Disease and FoodDisease datasets, where it achieved F-scores of 70.7% and 80.7%, respectively. Building on these performance results, LSD600 and the RE system trained on it can be valuable resources to fill the existing gap in this area and pave the way for downstream applications. Database URL: https://zenodo.org/records/13952449.</p>","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":"2025 ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11756709/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143001804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction to: The landscape of microRNA interaction annotation: analysis of three rare disorders as a case study.","authors":"","doi":"10.1093/database/baae131","DOIUrl":"https://doi.org/10.1093/database/baae131","url":null,"abstract":"","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":"2025 ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143969175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"HoloFood Data Portal: holo-omic datasets for analysing host-microbiota interactions in animal production.","authors":"Alexander B Rogers, Varsha Kale, Germana Baldi, Antton Alberdi, M Thomas P Gilbert, Dipayan Gupta, Morten T Limborg, Sen Li, Thomas Payne, Bent Petersen, Jacob A Rasmussen, Lorna Richardson, Robert D Finn","doi":"10.1093/database/baae112","DOIUrl":"https://doi.org/10.1093/database/baae112","url":null,"abstract":"<p><p>The HoloFood project used a hologenomic approach to understand the impact of host-microbiota interactions on salmon and chicken production by analysing multiomic data, phenotypic characteristics, and associated metadata in response to novel feeds. The project's raw data, derived analyses, and metadata are deposited in public, open archives (BioSamples, European Nucleotide Archive, MetaboLights, and MGnify), so making use of these diverse data types may require access to multiple resources. This is especially complex where analysis pipelines produce derived outputs such as functional profiles or genome catalogues. The HoloFood Data Portal is a web resource that simplifies access to the project datasets. For example, users can conveniently access multiomic datasets derived from the same individual or retrieve host phenotypic data with a linked gut microbiome sample. Project-specific metagenome-assembled genome and viral catalogues are also provided, linking to broader datasets in MGnify. The portal stores only data necessary to provide these relationships, with possible linking to the underlying repositories. The portal showcases a model approach for how future multiomics datasets can be made available. Database URL:  https://www.holofooddata.org.</p>","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":"2025 ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144126862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"DisGeNet: a disease-centric interaction database among diseases and various associated genes.","authors":"Yaxuan Hu, Xingli Guo, Yao Yun, Liang Lu, Xiaotai Huang, Songwei Jia","doi":"10.1093/database/baae122","DOIUrl":"10.1093/database/baae122","url":null,"abstract":"<p><p>The pathogenesis of complex diseases is intricately linked to various genes and network medicine has enhanced understanding of diseases. However, most network-based approaches ignore interactions mediated by noncoding RNAs (ncRNAs) and most databases only focus on the association between genes and diseases. Based on the mentioned questions, we have developed DisGeNet, a database focuses not only on the disease-associated genes but also on the interactions among genes. Here, the associations between diseases and various genes, as well as the interactions among these genes are integrated into a disease-centric network. As a result, there are a total of 502 688 interactions/associations involving 6697 diseases, 5780 lncRNAs (long noncoding RNAs), 16 135 protein-coding genes, and 2610 microRNAs stored in DisGeNet. These interactions/associations can be categorized as protein-protein, lncRNA-disease, microRNA-gene, microRNA-disease, gene-disease, and microRNA-lncRNA. Furthermore, as users input name/ID of diseases/genes for search, the interactions/associations about the search content can be browsed as a list or viewed in a local network-view. Database URL: https://disgenet.cn/.</p>","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":"2025 ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11724190/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142964005","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}