{"doi":"10.3389/fmicb.2025.1557285","title":"FACdb: a comprehensive resource for genes, gut microbiota, and metabolites in farm animals","abstract":"Farm animals, including livestock and poultry, play essential economic, social, and cultural roles and are indispensable in human welfare. Farm Animal Connectome database (FACdb) is a comprehensive resource that includes the association networks among gene expression, gut microbiota, and metabolites in farm animals. Although some databases present the relationship between gut microbes, metabolites, and gene expression, these databases are limited to human and mouse species, with limited data for farm animals. In this database, we calculate the associations and summarize the connections among gene expression, gut microbiota, and metabolites in farm animals using six correlation or distance calculation (including Pearson, Spearman, Cosine, Euclidean, Bray-Curtis, and Mahalanobis). FACdb contains over 55 million potential interactions of 73,571 genes, 11,046 gut microbiota, and 4,540 metabolites. It provides an easy-to-use interface for browsing and searching the association information. Additionally, FACdb offers interactive visualization tools to effectively investigate the relationship among the genes, gut microbiota, and metabolites in farm animals. Overall, FACdb is a valuable resource for understanding interactions among gut microbiota, metabolites, and gene expression. It contributes to the further utilization of microbes in animal products and welfare promotion. Compared to mice, pigs or other farm animals share more similarities with humans in molecular, cellular, and organ-level responses, indicating that our database may offer new insights into the relationship among gut microbiota, metabolites, and gene expression in humans.","journal":"Frontiers in Microbiology","year":2025,"id":2564,"datarank":0.10397207708399181,"base_score":0.6931471805599453,"endowment":0.6931471805599453,"self_citation_contribution":0.10397207708399181,"citation_network_contribution":0.0,"self_endowment_contribution":0.10397207708399181,"citer_contribution":0.0,"corpus_percentile":37.91700569568755,"corpus_rank":716,"citation_count":1,"citer_count":1,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.9439,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-03-21","fair_score":52.9167,"fair_percentile":79.11169744942832,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":28483,"name":"Yang Li","orcid":"0000-0003-4022-7341","position":1,"is_corresponding":false},{"id":30313,"name":"Di Zhang","orcid":"0000-0002-5704-4341","position":2,"is_corresponding":false},{"id":30314,"name":"Shuai Chen","orcid":"0000-0002-9337-6191","position":3,"is_corresponding":false},{"id":30315,"name":"Sien Lu","orcid":null,"position":4,"is_corresponding":false},{"id":30317,"name":"Miao Zhou","orcid":null,"position":6,"is_corresponding":false},{"id":30318,"name":"Zehe Song","orcid":null,"position":7,"is_corresponding":false},{"id":30319,"name":"Qingcui Li","orcid":null,"position":8,"is_corresponding":false},{"id":14718,"name":"Jie Yin","orcid":"0000-0002-4990-0777","position":9,"is_corresponding":false},{"id":30320,"name":"Xiaoping Liu","orcid":"0000-0002-3246-4227","position":10,"is_corresponding":false},{"id":30321,"name":"Lu Shi","orcid":"0000-0001-7397-8497","position":11,"is_corresponding":false},{"id":749,"name":"Hongen Kang","orcid":"0000-0002-9581-1329","position":12,"is_corresponding":false},{"id":30312,"name":"Ze Zhang","orcid":"0000-0002-8774-4867","position":0,"is_corresponding":true}],"reference_count":66,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-03-01T18:20:47.508186Z","pmid":"40190740","pmcid":"PMC11968756","fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":"gold","license":"cc-by","views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":65.0,"fair_a":67.5,"fair_i":37.5,"fair_r":41.6667,"fair_zscore":0.697,"fair_rationale":{"fair_score":52.92,"has_llm":true,"dimensions":{"F":{"name":"Findable","score":65.0,"criteria":[{"key":"f_has_doi","label":"Has a persistent DOI","kind":"deterministic","weight":1.0,"fraction":1.0,"signal":"DOI present","rationale":null},{"key":"f_repository_presence","label":"Indexed in repositories / literature DBs","kind":"deterministic","weight":1.0,"fraction":1.0,"signal":"datacite=0, pmcid=True, pmid=True","rationale":null},{"key":"f_persistent_ids","label":"Resolvable scholarly identifiers (OpenAlex)","kind":"deterministic","weight":0.5,"fraction":0.0,"signal":"no OpenAlex id","rationale":null},{"key":"f_metadata_richness","label":"Rich, machine-readable metadata","kind":"llm","weight":1.0,"fraction":0.5,"signal":null,"rationale":"The paper provides metadata such as species, sample counts, and external database links (e.g., STRING, NCBI Taxonomy, HMDB), but lacks machine-readable metadata formats like structured JSON-LD or schema.org annotations."}]},"A":{"name":"Accessible","score":67.5,"criteria":[{"key":"a_open_access","label":"Open Access / files deposited","kind":"deterministic","weight":1.5,"fraction":1.0,"signal":"Open Access","rationale":null},{"key":"a_retrievable","label":"Free full text retrievable","kind":"deterministic","weight":1.0,"fraction":0.0,"signal":"0 OA location(s)","rationale":null},{"key":"a_access_protocol","label":"Clear data/code access protocol","kind":"llm","weight":1.0,"fraction":0.75,"signal":null,"rationale":"The database is publicly accessible without login at two URLs, and the paper mentions open-access licensing (CC BY), but no explicit protocol for programmatic access or API is described."}]},"I":{"name":"Interoperable","score":37.5,"criteria":[{"key":"i_linked_data","label":"Linked datasets / DataCite relations","kind":"deterministic","weight":1.0,"fraction":0.0,"signal":"linked_datasets=0, datacite=0","rationale":null},{"key":"i_standard_ids","label":"References data via standard accessions","kind":"deterministic","weight":1.0,"fraction":0.0,"signal":"accessions=0, trials=0","rationale":null},{"key":"i_standards","label":"Standard formats, vocabularies & identifiers","kind":"llm","weight":1.0,"fraction":0.75,"signal":null,"rationale":"The paper uses standard formats (e.g., TPM for gene expression, relative abundance for microbiota) and references external databases (String-DB, NCBI Taxonomy, HMDB), but does not specify use of standard vocabularies or identifiers like MIxS or OBO."}]},"R":{"name":"Reusable","score":41.67,"criteria":[{"key":"r_license","label":"Clear, open reuse license","kind":"deterministic","weight":1.5,"fraction":0.0,"signal":"no license","rationale":null},{"key":"r_downloads","label":"Demonstrated reuse (downloads)","kind":"deterministic","weight":0.5,"fraction":0.0,"signal":"downloads=0","rationale":null},{"key":"r_version","label":"Versioned / maintained","kind":"deterministic","weight":0.5,"fraction":0.0,"signal":"no version chain","rationale":null},{"key":"r_dataset","label":"Classified as a data resource","kind":"deterministic","weight":0.5,"fraction":1.0,"signal":"is_dataset","rationale":null},{"key":"r_reusability","label":"Data-availability statement, license & reproducibility","kind":"llm","weight":2.0,"fraction":0.667,"signal":null,"rationale":"The paper includes a data-availability statement with open-access license (CC BY), provides download interface, and describes data processing steps, but lacks explicit code availability or reproducibility details for the correlation calculations."}]}},"suggestions":["Add machine-readable metadata (e.g., JSON-LD) with schema.org or Bioschemas for gene, microbiota, and metabolite data.","Provide a REST API or SPARQL endpoint for programmatic access to the association networks.","Use standard ontologies (e.g., NCBI Taxon, ChEBI, GO) for all entities and specify them in the data.","Include a code repository (e.g., GitHub) with scripts for data processing and correlation calculations.","Add a formal data citation with a persistent identifier (e.g., DOI) for the database itself."],"model":"deepseek/deepseek-v4-flash","agent_version":"fair_agent_v1","fulltext_source":"epmc_xml"},"fair_model":"deepseek/deepseek-v4-flash","fair_agent_version":"fair_agent_v1","fair_fulltext_source":"epmc_xml","fair_has_llm":true,"fair_computed_at":"2026-06-17T23:01:01.741492Z","clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}