Database: The Journal of Biological Databases and Curation最新文献_第4页

VarGuideAtlas: a repository of variant interpretation guidelines. VarGuideAtlas：变体解释指南资料库。

IF 3.4 4区生物学

Database: The Journal of Biological Databases and Curation Pub Date : 2025-03-11 DOI: 10.1093/database/baaf017

Mireia Costa, Alberto García S, Oscar Pastor

{"title":"VarGuideAtlas: a repository of variant interpretation guidelines.","authors":"Mireia Costa, Alberto García S, Oscar Pastor","doi":"10.1093/database/baaf017","DOIUrl":"10.1093/database/baaf017","url":null,"abstract":"Variant interpretation guidelines guide the process of determining the role of DNA variants in patients' health. Currently, hundreds of guidelines exist, each applicable to a particular clinical domain. However, they are scattered across multiple resources and scientific literature. To address this issue, we present VarGuideAtlas, a comprehensive repository of variant interpretation guidelines that compiles information from ClinGen, ClinVar, and PubMed. Our repository offers a user-friendly web interface with advanced search capabilities, enabling clinicians and researchers to efficiently find relevant guidelines tailored to specific genes, diseases, or variant types. We employ ontologies to characterize each guideline, ensuring consistency and improving interoperability with bioinformatics tools. VarGuideAtlas represents a significant advance toward standardizing variant interpretation practices, facilitating more informed decision-making, improved clinical outcomes, and more precise genomic research. VarGuideAtlas is publicly accessible via a web-based platform (https://genomics-hub.pros.dsic.upv.es:3016/).","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":"2025 ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11895764/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143604068","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}

引用次数: 0

VarGuideAtlas: a repository of variant interpretation guidelines. VarGuideAtlas：一个变体解释指南的存储库。

IF 3.4 4区生物学

Database: The Journal of Biological Databases and Curation Pub Date : 2025-03-11 DOI: 10.1093/database/baaf017

Mireia Costa, Alberto García S, Oscar Pastor

{"title":"VarGuideAtlas: a repository of variant interpretation guidelines.","authors":"Mireia Costa, Alberto García S, Oscar Pastor","doi":"10.1093/database/baaf017","DOIUrl":"https://doi.org/10.1093/database/baaf017","url":null,"abstract":"Variant interpretation guidelines guide the process of determining the role of DNA variants in patients' health. Currently, hundreds of guidelines exist, each applicable to a particular clinical domain. However, they are scattered across multiple resources and scientific literature. To address this issue, we present VarGuideAtlas, a comprehensive repository of variant interpretation guidelines that compiles information from ClinGen, ClinVar, and PubMed. Our repository offers a user-friendly web interface with advanced search capabilities, enabling clinicians and researchers to efficiently find relevant guidelines tailored to specific genes, diseases, or variant types. We employ ontologies to characterize each guideline, ensuring consistency and improving interoperability with bioinformatics tools. VarGuideAtlas represents a significant advance toward standardizing variant interpretation practices, facilitating more informed decision-making, improved clinical outcomes, and more precise genomic research. VarGuideAtlas is publicly accessible via a web-based platform (https://genomics-hub.pros.dsic.upv.es:3016/).","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":"2025 ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144126926","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}

引用次数: 0

Pipeline to explore information on genome editing using large language models and genome editing meta-database. 利用大型语言模型和基因组编辑元数据库探索基因组编辑信息的管道。

IF 3.4 4区生物学

Database: The Journal of Biological Databases and Curation Pub Date : 2025-03-08 DOI: 10.1093/database/baaf022

Takayuki Suzuki, Hidemasa Bono

{"title":"Pipeline to explore information on genome editing using large language models and genome editing meta-database.","authors":"Takayuki Suzuki, Hidemasa Bono","doi":"10.1093/database/baaf022","DOIUrl":"https://doi.org/10.1093/database/baaf022","url":null,"abstract":"Genome editing (GE) is widely recognized as an effective and valuable technology in life sciences research. However, certain genes are difficult to edit depending on some factors such as the type of species, sequences, and GE tools. Therefore, confirming the presence or absence of GE practices in previous publications is crucial for the effective designing and establishment of research using GE. Although the Genome Editing Meta-database (GEM: https://bonohu.hiroshima-u.ac.jp/gem/) aims to provide as comprehensive GE information as possible, it does not indicate how each registered gene is involved in GE. In this study, we developed a systematic method for extracting essential GE information using large language models from the information based on GEM and GE-related articles. This approach allows for a systematic and efficient investigation of GE information that cannot be achieved using the current GEM alone. In addition, by converting the extracted GE information into metrics, we propose a potential application of this method to prioritize genes for future research. The extracted GE information and novel GE-related scores are expected to facilitate the efficient selection of target genes for GE and support the design of research using GE. Database URLs: https://github.com/szktkyk/extract_geinfo, https://github.com/szktkyk/visualize_geinfo.","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":"2025 ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144126878","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}

引用次数: 0

Pipeline to explore information on genome editing using large language models and genome editing meta-database. 利用大型语言模型和基因组编辑元数据库探索基因组编辑信息的管道。

IF 3.4 4区生物学

Database: The Journal of Biological Databases and Curation Pub Date : 2025-03-08 DOI: 10.1093/database/baaf022

Takayuki Suzuki, Hidemasa Bono

{"title":"Pipeline to explore information on genome editing using large language models and genome editing meta-database.","authors":"Takayuki Suzuki, Hidemasa Bono","doi":"10.1093/database/baaf022","DOIUrl":"10.1093/database/baaf022","url":null,"abstract":"Genome editing (GE) is widely recognized as an effective and valuable technology in life sciences research. However, certain genes are difficult to edit depending on some factors such as the type of species, sequences, and GE tools. Therefore, confirming the presence or absence of GE practices in previous publications is crucial for the effective designing and establishment of research using GE. Although the Genome Editing Meta-database (GEM: https://bonohu.hiroshima-u.ac.jp/gem/) aims to provide as comprehensive GE information as possible, it does not indicate how each registered gene is involved in GE. In this study, we developed a systematic method for extracting essential GE information using large language models from the information based on GEM and GE-related articles. This approach allows for a systematic and efficient investigation of GE information that cannot be achieved using the current GEM alone. In addition, by converting the extracted GE information into metrics, we propose a potential application of this method to prioritize genes for future research. The extracted GE information and novel GE-related scores are expected to facilitate the efficient selection of target genes for GE and support the design of research using GE. Database URLs: https://github.com/szktkyk/extract_geinfo, https://github.com/szktkyk/visualize_geinfo.","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":"2025 ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11890094/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143582230","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}

引用次数: 0

gymnotoa-db: a database and application to optimize functional annotation in gymnosperms. Gymnotoa-db：一个优化裸子植物功能注释的数据库和应用程序。

IF 3.4 4区生物学

Database: The Journal of Biological Databases and Curation Pub Date : 2025-03-05 DOI: 10.1093/database/baaf019

Fernando Mora-Márquez, Mikel Hurtado, Unai López de Heredia

{"title":"gymnotoa-db: a database and application to optimize functional annotation in gymnosperms.","authors":"Fernando Mora-Márquez, Mikel Hurtado, Unai López de Heredia","doi":"10.1093/database/baaf019","DOIUrl":"10.1093/database/baaf019","url":null,"abstract":"Gymnosperms are a clade of non-flowering plants that include about 1000 living species. Due to their complex genomes and lack of genomic resources, functional annotation in genomics and transcriptomics on gymnosperms suffers from limitations. Here we present gymnotoa-db, which is a novel, publicly accessible relational database designed to facilitate functional annotation in gymnosperms. This database stores non-redundant records of gymnosperm proteins, encompassing taxonomic and functional information. The complementary software, gymnotoa-app, enables users to download gymnotoa-db and execute a comprehensive functional annotation pipeline for high-throughput sequencing-derived DNA or cDNA sequences. gymnotoa-app's user-friendly interface and efficient algorithms streamline the functional annotation process, making it an invaluable tool for researchers studying gymnosperms. We compared gymnotoa-app's performance against other annotation tools utilizing disparate reference databases. Our results demonstrate gymnotoa-app's superior ability to accurately annotate gymnosperm transcripts, recovering a greater number of transcripts and unique, non-redundant Gene Ontology terms. gymnotoa-db's distinctive features include comprehensive coverage with a non-redundant dataset of gymnosperm protein sequences, robust functional information that integrates data from multiple ontology systems, including GO, KEGG, EC, and MetaCYC, while keeping the taxonomic context, including Arabidopsis homologs. Database URL: https://blogs.upm.es/gymnotoa-db/2024/09/19/gymnotoa-app/.","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":"2025 ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11886576/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143572429","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}

引用次数: 0

gymnotoa-db: a database and application to optimize functional annotation in gymnosperms. Gymnotoa-db：一个优化裸子植物功能注释的数据库和应用程序。

IF 3.4 4区生物学

Database: The Journal of Biological Databases and Curation Pub Date : 2025-03-05 DOI: 10.1093/database/baaf019

Fernando Mora-Márquez, Mikel Hurtado, Unai López de Heredia

{"title":"gymnotoa-db: a database and application to optimize functional annotation in gymnosperms.","authors":"Fernando Mora-Márquez, Mikel Hurtado, Unai López de Heredia","doi":"10.1093/database/baaf019","DOIUrl":"https://doi.org/10.1093/database/baaf019","url":null,"abstract":"Gymnosperms are a clade of non-flowering plants that include about 1000 living species. Due to their complex genomes and lack of genomic resources, functional annotation in genomics and transcriptomics on gymnosperms suffers from limitations. Here we present gymnotoa-db, which is a novel, publicly accessible relational database designed to facilitate functional annotation in gymnosperms. This database stores non-redundant records of gymnosperm proteins, encompassing taxonomic and functional information. The complementary software, gymnotoa-app, enables users to download gymnotoa-db and execute a comprehensive functional annotation pipeline for high-throughput sequencing-derived DNA or cDNA sequences. gymnotoa-app's user-friendly interface and efficient algorithms streamline the functional annotation process, making it an invaluable tool for researchers studying gymnosperms. We compared gymnotoa-app's performance against other annotation tools utilizing disparate reference databases. Our results demonstrate gymnotoa-app's superior ability to accurately annotate gymnosperm transcripts, recovering a greater number of transcripts and unique, non-redundant Gene Ontology terms. gymnotoa-db's distinctive features include comprehensive coverage with a non-redundant dataset of gymnosperm protein sequences, robust functional information that integrates data from multiple ontology systems, including GO, KEGG, EC, and MetaCYC, while keeping the taxonomic context, including Arabidopsis homologs. Database URL: https://blogs.upm.es/gymnotoa-db/2024/09/19/gymnotoa-app/.","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":"2025 ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144126842","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}

引用次数: 0

ForestForward: visualizing and accessing integrated world forest data from the last 50 years. ForestForward：可视化和访问过去50年的综合世界森林数据。

IF 3.4 4区生物学

Database: The Journal of Biological Databases and Curation Pub Date : 2025-03-03 DOI: 10.1093/database/baaf018

E L Tejada-Gutiérrez, J Mateo Fornés, F Solsona, R Alves

{"title":"ForestForward: visualizing and accessing integrated world forest data from the last 50 years.","authors":"E L Tejada-Gutiérrez, J Mateo Fornés, F Solsona, R Alves","doi":"10.1093/database/baaf018","DOIUrl":"https://doi.org/10.1093/database/baaf018","url":null,"abstract":"Mitigating the effects of environmental exploitation on forests requires robust data analysis tools to inform sustainable management strategies and enhance ecosystem resilience. Access to extensive, integrated plant biodiversity data, spanning decades, is essential for this purpose. However, such data are often fragmented across diverse datasets with varying standards, posing two key challenges: first, integrating these datasets into a unified, well-structured data warehouse, and second, handling the vast volume of data using big data technologies to analyze and monitor the temporal evolution of ecosystems. To address these challenges, we developed and used an extract, transform, and load (ETL) protocol that curated and integrates 4482 forestry datasets from around the world, dating back to the 18th century, into a 100-GB data warehouse containing over 172 million records sourced from the Global Biodiversity Information Facility repository. We implemented Python scripts and a NoSQL MongoDB database to streamline and automate the ETL process, using the data warehouse to create the ForestForward web platform. ForestForward is a free, user-friendly application developed using the Django framework, which enables users to consult, download, and visualize the curated data. The platform allows users to explore data layers by year and observe the temporal evolution of ecosystems through visual representations. Database URL: https://forestforward.udl.cat.","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":"2025 ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144126751","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}

引用次数: 0

ForestForward: visualizing and accessing integrated world forest data from the last 50 years. ForestForward：可视化和访问过去50年的综合世界森林数据。

IF 3.4 4区生物学

Database: The Journal of Biological Databases and Curation Pub Date : 2025-03-03 DOI: 10.1093/database/baaf018

E L Tejada-Gutiérrez, J Mateo Fornés, F Solsona, R Alves

{"title":"ForestForward: visualizing and accessing integrated world forest data from the last 50 years.","authors":"E L Tejada-Gutiérrez, J Mateo Fornés, F Solsona, R Alves","doi":"10.1093/database/baaf018","DOIUrl":"10.1093/database/baaf018","url":null,"abstract":"Mitigating the effects of environmental exploitation on forests requires robust data analysis tools to inform sustainable management strategies and enhance ecosystem resilience. Access to extensive, integrated plant biodiversity data, spanning decades, is essential for this purpose. However, such data are often fragmented across diverse datasets with varying standards, posing two key challenges: first, integrating these datasets into a unified, well-structured data warehouse, and second, handling the vast volume of data using big data technologies to analyze and monitor the temporal evolution of ecosystems. To address these challenges, we developed and used an extract, transform, and load (ETL) protocol that curated and integrates 4482 forestry datasets from around the world, dating back to the 18th century, into a 100-GB data warehouse containing over 172 million records sourced from the Global Biodiversity Information Facility repository. We implemented Python scripts and a NoSQL MongoDB database to streamline and automate the ETL process, using the data warehouse to create the ForestForward web platform. ForestForward is a free, user-friendly application developed using the Django framework, which enables users to consult, download, and visualize the curated data. The platform allows users to explore data layers by year and observe the temporal evolution of ecosystems through visual representations. Database URL: https://forestforward.udl.cat.","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":"2025 ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11879282/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143556257","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}

引用次数: 0

TcEVdb: a database for T-cell-derived small extracellular vesicles from single-cell transcriptomes. TcEVdb：来自单细胞转录组的t细胞衍生的小细胞外囊泡数据库。

IF 3.4 4区生物学

Database: The Journal of Biological Databases and Curation Pub Date : 2025-02-28 DOI: 10.1093/database/baaf012

Tao Luo, Wen-Kang Shen, Chu-Yu Zhang, Dan-Dan Song, Xiu-Qing Zhang, An-Yuan Guo, Qian Lei

{"title":"TcEVdb: a database for T-cell-derived small extracellular vesicles from single-cell transcriptomes.","authors":"Tao Luo, Wen-Kang Shen, Chu-Yu Zhang, Dan-Dan Song, Xiu-Qing Zhang, An-Yuan Guo, Qian Lei","doi":"10.1093/database/baaf012","DOIUrl":"10.1093/database/baaf012","url":null,"abstract":"T-Cell-derived extracellular vesicles (TcEVs) play key roles in immune regulation and tumor microenvironment modulation. However, the heterogeneity of TcEV remains poorly understood due to technical limitations of EV analysis and the lack of comprehensive data. To address this, we constructed TcEVdb, a comprehensive database that explores the expression and cluster of TcEV by the SEVtras method from T-cell single-cell RNA sequencing data. TcEVdb contains 277 265 EV droplets from 51 T-cell types across 221 samples from 21 projects, covering 9 tissue sources and 23 disease conditions. The database provides two main functional modules. The Browse module enables users to investigate EV secretion activity indices across samples, visualize TcEV clusters, analyze differentially expressed genes (DEGs) and pathway enrichment in TcEV subpopulations, and compare TcEV transcriptomes with their cellular origins. The Search module allows users to query specific genes across all datasets and visualize their expression distribution. Furthermore, our analysis of TcEV in diffuse large B-cell lymphoma revealed increased EV secretion in CD4+ T exhausted cells compared to healthy controls. Subsequent analyses identified distinct droplet clusters with differential expression genes, including clusters enriched for genes associated with cell motility and mitochondrial function. Overall, TcEVdb serves as a comprehensive resource for exploring the transcriptome of TcEV, which will contribute to advancements in EV-based diagnostics and therapeutics across a wide range of diseases. Database URL: https://guolab.wchscu.cn/TcEVdb.","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":"2025 ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11885782/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143555417","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}

引用次数: 0

TcEVdb: a database for T-cell-derived small extracellular vesicles from single-cell transcriptomes. TcEVdb：来自单细胞转录组的t细胞衍生的小细胞外囊泡数据库。

IF 3.4 4区生物学

Database: The Journal of Biological Databases and Curation Pub Date : 2025-02-28 DOI: 10.1093/database/baaf012

Tao Luo, Wen-Kang Shen, Chu-Yu Zhang, Dan-Dan Song, Xiu-Qing Zhang, An-Yuan Guo, Qian Lei

{"title":"TcEVdb: a database for T-cell-derived small extracellular vesicles from single-cell transcriptomes.","authors":"Tao Luo, Wen-Kang Shen, Chu-Yu Zhang, Dan-Dan Song, Xiu-Qing Zhang, An-Yuan Guo, Qian Lei","doi":"10.1093/database/baaf012","DOIUrl":"https://doi.org/10.1093/database/baaf012","url":null,"abstract":"T-Cell-derived extracellular vesicles (TcEVs) play key roles in immune regulation and tumor microenvironment modulation. However, the heterogeneity of TcEV remains poorly understood due to technical limitations of EV analysis and the lack of comprehensive data. To address this, we constructed TcEVdb, a comprehensive database that explores the expression and cluster of TcEV by the SEVtras method from T-cell single-cell RNA sequencing data. TcEVdb contains 277 265 EV droplets from 51 T-cell types across 221 samples from 21 projects, covering 9 tissue sources and 23 disease conditions. The database provides two main functional modules. The Browse module enables users to investigate EV secretion activity indices across samples, visualize TcEV clusters, analyze differentially expressed genes (DEGs) and pathway enrichment in TcEV subpopulations, and compare TcEV transcriptomes with their cellular origins. The Search module allows users to query specific genes across all datasets and visualize their expression distribution. Furthermore, our analysis of TcEV in diffuse large B-cell lymphoma revealed increased EV secretion in CD4+ T exhausted cells compared to healthy controls. Subsequent analyses identified distinct droplet clusters with differential expression genes, including clusters enriched for genes associated with cell motility and mitochondrial function. Overall, TcEVdb serves as a comprehensive resource for exploring the transcriptome of TcEV, which will contribute to advancements in EV-based diagnostics and therapeutics across a wide range of diseases. Database URL: https://guolab.wchscu.cn/TcEVdb.","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":"2025 ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144126920","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}

引用次数: 0