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

{"title":"Aerial Wildlife Image Repository for animal monitoring with drones in the age of artificial intelligence.","authors":"Sathishkumar Samiappan, B Santhana Krishnan, Damion Dehart, Landon R Jones, Jared A Elmore, Kristine O Evans, Raymond B Iglay","doi":"10.1093/database/baae070","DOIUrl":"10.1093/database/baae070","url":null,"abstract":"<p><p>Drones (unoccupied aircraft systems) have become effective tools for wildlife monitoring and conservation. Automated animal detection and classification using artificial intelligence (AI) can substantially reduce logistical and financial costs and improve drone surveys. However, the lack of annotated animal imagery for training AI is a critical bottleneck in achieving accurate performance of AI algorithms compared to other fields. To bridge this gap for drone imagery and help advance and standardize automated animal classification, we have created the Aerial Wildlife Image Repository (AWIR), which is a dynamic, interactive database with annotated images captured from drone platforms using visible and thermal cameras. The AWIR provides the first open-access repository for users to upload, annotate, and curate images of animals acquired from drones. The AWIR also provides annotated imagery and benchmark datasets that users can download to train AI algorithms to automatically detect and classify animals, and compare algorithm performance. The AWIR contains 6587 animal objects in 1325 visible and thermal drone images of predominantly large birds and mammals of 13 species in open areas of North America. As contributors increase the taxonomic and geographic diversity of available images, the AWIR will open future avenues for AI research to improve animal surveys using drones for conservation applications. Database URL: https://projectportal.gri.msstate.edu/awir/.</p>","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11265857/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141751327","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":"PPCRKB: a risk factor knowledge base of postoperative pulmonary complications.","authors":"Jianchao Duan, Peiyi Li, Aibin Shao, Xuechao Hao, Ruihao Zhou, Cheng Bi, Xingyun Liu, Weimin Li, Huadong Zhu, Guo Chen, Bairong Shen, Tao Zhu","doi":"10.1093/database/baae054","DOIUrl":"10.1093/database/baae054","url":null,"abstract":"<p><p>Postoperative pulmonary complications (PPCs) are highly heterogeneous disorders with diverse risk factors frequently occurring after surgical interventions, resulting in significant financial burdens, prolonged hospitalization and elevated mortality rates. Despite the existence of multiple studies on PPCs, a comprehensive knowledge base that can effectively integrate and visualize the diverse risk factors associated with PPCs is currently lacking. This study aims to develop an online knowledge platform on risk factors for PPCs (Postoperative Pulmonary Complications Risk Factor Knowledge Base, PPCRKB) that categorizes and presents the risk and protective factors associated with PPCs, as well as to facilitate the development of individualized prevention and management strategies for PPCs based on the needs of each investigator. The PPCRKB is a novel knowledge base that encompasses all investigated potential risk factors linked to PPCs, offering users a web-based platform to access these risk factors. The PPCRKB contains 2673 entries, 915 risk factors that have been categorized into 11 distinct groups. These categories include habit and behavior, surgical factors, anesthetic factors, auxiliary examination, environmental factors, clinical status, medicines and treatment, demographic characteristics, psychosocial factors, genetic factors and miscellaneous factors. The PPCRKB holds significant value for PPC research. The inclusion of both quantitative and qualitative data in the PPCRKB enhances the ability to uncover new insights and solutions related to PPCs. It could provide clinicians with a more comprehensive perspective on research related to PPCs in future. Database URL: http://sysbio.org.cn/PPCs.</p>","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11259045/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141726929","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":"MIAMI-AD (Methylation in Aging and Methylation in AD): an integrative knowledgebase that facilitates explorations of DNA methylation across sex, aging, and Alzheimer's disease.","authors":"David Lukacsovich, Deirdre O'Shea, Hanchen Huang, Wei Zhang, Juan Young, X Steven Chen, Sven-Thorsten Dietrich, Brian Kunkle, Eden Martin, Lily Wang","doi":"10.1093/database/baae061","DOIUrl":"10.1093/database/baae061","url":null,"abstract":"<p><p>Alzheimer's disease (AD) is a common neurodegenerative disorder with a significant impact on aging populations. DNA methylation (DNAm) alterations have been implicated in both the aging processes and the development of AD. Given that AD affects more women than men, it is also important to explore DNAm changes that occur specifically in each sex. We created MIAMI-AD, a comprehensive knowledgebase containing manually curated summary statistics from 98 published tables in 38 studies, all of which included at least 100 participants. MIAMI-AD enables easy browsing, querying, and downloading DNAm associations at multiple levels-at individual CpG, gene, genomic regions, or genome-wide, in one or multiple studies. Moreover, it also offers tools to perform integrative analyses, such as comparing DNAm associations across different phenotypes or tissues, as well as interactive visualizations. Using several use case examples, we demonstrated that MIAMI-AD facilitates our understanding of age-associated CpGs in AD and the sex-specific roles of DNAm in AD. This open-access resource is freely available to the research community, and all the underlying data can be downloaded. MIAMI-AD facilitates integrative explorations to better understand the interplay between DNAm across aging, sex, and AD. Database URL: https://miami-ad.org/.</p>","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11259044/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141726928","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":"HOFE: an interactive forensic entomological database.","authors":"Mandie Liu, Yihong Qu, Yifei Luo, Binta J J Jallow, Yuting Ma, Afito Luciano, Jingjing Huang, Jifeng Cai, Fanming Meng","doi":"10.1093/database/baae058","DOIUrl":"10.1093/database/baae058","url":null,"abstract":"<p><p>The significance of entomological evidence in inferring the time, location and cause of death has been demonstrated both theoretically and practically. With the advancement of sequencing technologies, reports have emerged on necrophagous insects' nuclear genomes, transcriptomes, proteomes and mitochondrial genomes. However, within the field of forensic entomology, there is currently no available database that can integrate, store and share the resources of necrophagous insects. The absence of a database poses an inconvenience to the application of entomological evidence in judicial practice and hampers the development of the forensic entomology discipline. Given this, we have developed the Home Of Forensic Entomology database, encompassing 10 core functional modules: Home, Browse, Mitochondria, Proteome, JBrowse, Search, BLAST, Tools, Case base and Maps. Notably, the 'Tools' module enables multiple sequence alignment analysis (Muscle), homologous protein prediction (Genewise), primer design (Primer), large-scale genomic analysis (Lastz), Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis, as well as expression profiling (PCA Analysis, Hcluster and Correlation Heatmap). In addition, the present database also works as an interactive platform for researchers by sharing forensic entomological case reports and uploading data and material. This database provides potential visitors with a comprehensive function for multi-omics data analysis, offers substantial references to researchers and criminal scene investigators and facilitates the utilization of entomological evidence in court. Database URL: http://ihofe.com/.</p>","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11245407/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141598848","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":"Towards discovery: an end-to-end system for uncovering novel biomedical relations.","authors":"Tiago Almeida, Richard A A Jonker, Rui Antunes, João R Almeida, Sérgio Matos","doi":"10.1093/database/baae057","DOIUrl":"10.1093/database/baae057","url":null,"abstract":"<p><p>Biomedical relation extraction is an ongoing challenge within the natural language processing community. Its application is important for understanding scientific biomedical literature, with many use cases, such as drug discovery, precision medicine, disease diagnosis, treatment optimization and biomedical knowledge graph construction. Therefore, the development of a tool capable of effectively addressing this task holds the potential to improve knowledge discovery by automating the extraction of relations from research manuscripts. The first track in the BioCreative VIII competition extended the scope of this challenge by introducing the detection of novel relations within the literature. This paper describes that our participation system initially focused on jointly extracting and classifying novel relations between biomedical entities. We then describe our subsequent advancement to an end-to-end model. Specifically, we enhanced our initial system by incorporating it into a cascading pipeline that includes a tagger and linker module. This integration enables the comprehensive extraction of relations and classification of their novelty directly from raw text. Our experiments yielded promising results, and our tagger module managed to attain state-of-the-art named entity recognition performance, with a micro F1-score of 90.24, while our end-to-end system achieved a competitive novelty F1-score of 24.59. The code to run our system is publicly available at https://github.com/ieeta-pt/BioNExt. Database URL: https://github.com/ieeta-pt/BioNExt.</p>","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11240158/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141589889","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":"DrugRepoBank: a comprehensive database and discovery platform for accelerating drug repositioning.","authors":"Yixian Huang, Danhong Dong, Wenyang Zhang, Ruiting Wang, Yang-Chi-Dung Lin, Huali Zuo, Hsi-Yuan Huang, Hsien-Da Huang","doi":"10.1093/database/baae051","DOIUrl":"10.1093/database/baae051","url":null,"abstract":"<p><p>In recent years, drug repositioning has emerged as a promising alternative to the time-consuming, expensive and risky process of developing new drugs for diseases. However, the current database for drug repositioning faces several issues, including insufficient data volume, restricted data types, algorithm inaccuracies resulting from the neglect of multidimensional or heterogeneous data, a lack of systematic organization of literature data associated with drug repositioning, limited analytical capabilities and user-unfriendly webpage interfaces. Hence, we have established the first all-encompassing database called DrugRepoBank, consisting of two main modules: the 'Literature' module and the 'Prediction' module. The 'Literature' module serves as the largest repository of literature-supported drug repositioning data with experimental evidence, encompassing 169 repositioned drugs from 134 articles from 1 January 2000 to 1 July 2023. The 'Prediction' module employs 18 efficient algorithms, including similarity-based, artificial-intelligence-based, signature-based and network-based methods to predict repositioned drug candidates. The DrugRepoBank features an interactive and user-friendly web interface and offers comprehensive functionalities such as bioinformatics analysis of disease signatures. When users provide information about a drug, target or disease of interest, DrugRepoBank offers new indications and targets for the drug, proposes new drugs that bind to the target or suggests potential drugs for the queried disease. Additionally, it provides basic information about drugs, targets or diseases, along with supporting literature. We utilize three case studies to demonstrate the feasibility and effectiveness of predictively repositioned drugs within DrugRepoBank. The establishment of the DrugRepoBank database will significantly accelerate the pace of drug repositioning. Database URL:  https://awi.cuhk.edu.cn/DrugRepoBank.</p>","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11240114/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141589856","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":"ImmRNA: a database of RNAs associated with tumor immunity.","authors":"Fangfang Shen, Zelian Li, Pengfei Wu, Jinpeng Wang","doi":"10.1093/database/baae052","DOIUrl":"10.1093/database/baae052","url":null,"abstract":"<p><p>The relationship between different ribonucleic acids (RNAs) and tumor immunity has been widely investigated. However, a systematic description of tumor immune-related RNAs in different tumors is still lacking. We collected the relationship of tumor immune-related RNAs from the published literature and presented them in a user-friendly interface, \"ImmRNA\" (http://www.immrna.cn/), to provide a resource to study immune-RNA-cancer regulatory relations. The ImmRNA contains 49 996 curated entries. Each entry includes gene symbols, gene types, target genes, downstream effects, functions, immune cells, and other information. By rearranging and reanalyzing the data, our dataset contains the following key points: (i) providing the links between RNAs and the immune in cancers, (ii) displaying the downstream effects and functions of RNAs, (iii) listing immune cells and immune pathways related to RNA function, (iv) showing the relationship between RNAs and prognostic outcomes, and (v) exhibiting the experimental methods described in the article. ImmRNA provides a valuable resource for understanding the functions of tumor immune-related RNAs. Database URL:  http://www.immrna.cn/.</p>","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11227110/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141544688","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":"SpadaHC: a database to improve the classification of variants in hereditary cancer genes in the Spanish population.","authors":"José M Moreno-Cabrera, Lidia Feliubadaló, Marta Pineda, Patricia Prada-Dacasa, Mireia Ramos-Muntada, Jesús Del Valle, Joan Brunet, Bernat Gel, María Currás-Freixes, Bruna Calsina, Milton E Salazar-Hidalgo, Marta Rodríguez-Balada, Bàrbara Roig, Sara Fernández-Castillejo, Mercedes Durán Domínguez, Mónica Arranz Ledo, Mar Infante Sanz, Adela Castillejo, Estela Dámaso, José L Soto, Montserrat de Miguel, Beatriz Hidalgo Calero, José M Sánchez-Zapardiel, Teresa Ramon Y Cajal, Adriana Lasa, Alexandra Gisbert-Beamud, Anael López-Novo, Clara Ruiz-Ponte, Miriam Potrony, María I Álvarez-Mora, Ana Osorio, Isabel Lorda-Sánchez, Mercedes Robledo, Alberto Cascón, Anna Ruiz, Nino Spataro, Imma Hernan, Emma Borràs, Alejandro Moles-Fernández, Julie Earl, Juan Cadiñanos, Ana B Sánchez-Heras, Anna Bigas, Gabriel Capellá, Conxi Lázaro","doi":"10.1093/database/baae055","DOIUrl":"10.1093/database/baae055","url":null,"abstract":"<p><p>Accurate classification of genetic variants is crucial for clinical decision-making in hereditary cancer. In Spain, genetic diagnostic laboratories have traditionally approached this task independently due to the lack of a dedicated resource. Here we present SpadaHC, a web-based database for sharing variants in hereditary cancer genes in the Spanish population. SpadaHC is implemented using a three-tier architecture consisting of a relational database, a web tool and a bioinformatics pipeline. Contributing laboratories can share variant classifications and variants from individuals in Variant Calling Format (VCF) format. The platform supports open and restricted access, flexible dataset submissions, automatic pseudo-anonymization, VCF quality control, variant normalization and liftover between genome builds. Users can flexibly explore and search data, receive automatic discrepancy notifications and access SpadaHC population frequencies based on many criteria. In February 2024, SpadaHC included 18 laboratory members, storing 1.17 million variants from 4306 patients and 16 343 laboratory classifications. In the first analysis of the shared data, we identified 84 genetic variants with clinically relevant discrepancies in their classifications and addressed them through a three-phase resolution strategy. This work highlights the importance of data sharing to promote consistency in variant classifications among laboratories, so patients and family members can benefit from more accurate clinical management. Database URL: https://spadahc.ciberisciii.es/.</p>","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11223915/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141533924","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":"MyxoPortal: a database of myxobacterial genomic features.","authors":"Rayapadi G Swetha, Benita S Arakal, Santhosh Rajendran, K Sekar, David E Whitworth, Sudha Ramaiah, Philip E James, Paul G Livingstone, Anand Anbarasu","doi":"10.1093/database/baae056","DOIUrl":"10.1093/database/baae056","url":null,"abstract":"<p><p>Myxobacteria are predatory bacteria with antimicrobial activity, utilizing complex mechanisms to kill their prey and assimilate their macromolecules. Having large genomes encoding hundreds of secondary metabolites, hydrolytic enzymes and antimicrobial peptides, these organisms are widely studied for their antibiotic potential. MyxoPortal is a comprehensive genomic database hosting 262 genomes of myxobacterial strains. Datasets included provide genome annotations with gene locations, functions, amino acids and nucleotide sequences, allowing analysis of evolutionary and taxonomical relationships between strains and genes. Biosynthetic gene clusters are identified by AntiSMASH, and dbAMP-generated antimicrobial peptide sequences are included as a resource for novel antimicrobial discoveries, while curated datasets of CRISPR/Cas genes, regulatory protein sequences, and phage associated genes give useful insights into each strain's biological properties. MyxoPortal is an intuitive open-source database that brings together application-oriented genomic features that can be used in taxonomy, evolution, predation and antimicrobial research. MyxoPortal can be accessed at http://dicsoft1.physics.iisc.ac.in/MyxoPortal/. Database URL:  http://dicsoft1.physics.iisc.ac.in/MyxoPortal/. Graphical Abstract.</p>","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11219305/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141491208","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":"ISTransbase: an online database for inhibitor and substrate of drug transporters.","authors":"Jinfu Peng, Jiacai Yi, Guoping Yang, Zhijun Huang, Dongsheng Cao","doi":"10.1093/database/baae053","DOIUrl":"https://doi.org/10.1093/database/baae053","url":null,"abstract":"<p><p>Drug transporters, integral membrane proteins found throughout the human body, play critical roles in physiological and biochemical processes through interactions with ligands, such as substrates and inhibitors. The extensive and disparate data on drug transporters complicate understanding their complex relationships with ligands. To address this challenge, it is essential to gather and summarize information on drug transporters, inhibitors and substrates, and simultaneously develop a comprehensive and user-friendly database. Current online resources often provide fragmented information and have limited coverage of drug transporter substrates and inhibitors, highlighting the need for a specialized, comprehensive and openly accessible database. ISTransbase addresses this gap by amassing a substantial amount of data from literature, government documents and open databases. It includes 16 528 inhibitors and 4465 substrates of 163 drug transporters from 18 different species, resulting in a total of 93 841 inhibitor records and 51 053 substrate records. ISTransbase provides detailed insights into drug transporters and their inhibitors/substrates, encompassing transporter and molecule structure, transporter function and distribution, as well as experimental methods and results from transport or inhibition experiments. Furthermore, ISTransbase offers three search strategies that allow users to retrieve drugs and transporters based on multiple selectable constraints, as well as perform checks for drug-drug interactions. Users can also browse and download data. In summary, ISTransbase (https://istransbase.scbdd.com/) serves as a valuable resource for accurately and efficiently accessing information on drug transporter inhibitors and substrates, aiding researchers in exploring drug transporter mechanisms and assisting clinicians in mitigating adverse drug reactions Database URL: https://istransbase.scbdd.com/.</p>","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11214160/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141466807","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}