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At least 19 recordsLinked to original sources

PubMed2026

A single-cell meta-analysis evidences transposable element dysregulation in sex-based differences in Parkinson's disease.

Transposable elements (TEs) (mobile genetic elements comprising ∼45% of the human genome) have recently emerged as potential contributors to Parkinson's disease (PD); however their role and sex-specific impact remain poorly understood. Here, we present the first integrative meta-analysis of TE expression across 4 substantia nigra single-nucleus RNA-seq datasets, comprising a total of 66 donors, generating a cell-type-resolved atlas of TE dysregulation in PD. We identified widespread TE activation across major brain cell types (i.e. neurons, astrocytes, oligodendrocytes and microglia), with marked upregulation of L1s in neurons and HERVs in oligodendrocytes. Sex-stratified analyses revealed distinct male- and female-biased TE signatures, indicating regulatory programs uniquely affected in each sex, including MIR elements in microglia and Alu subfamilies in neurons. Correlation and genomic proximity analyses also uncovered TE-gene associations linked to important PD pathways such as neuroinflammation or myelination. Collectively, our study positions TEs as potential sex-modulated contributors to PD pathology and also provides a public web resource (PATOSS) to explore PD-associated TE transcriptional deregulation.

Parkinson's disease↗

PubMed2026

eQTM (expression quantitative trait methylation) Atlas: a comprehensive resource of over 11 million DNA methylation-gene expression associations through across 11 tissues and 4 diseases.

MOTIVATION: Epigenome-wide association studies (EWAS) have identified numerous DNA methylation (DNAm) CpG sites associated with complex traits and diseases, but interpretation of those CpG sites remains challenging because in EWAS, CpGs are mostly linked to nearby genes based only on genomic proximity. Expression quantitative trait methylation (eQTM) analyses connect DNAm CpGs with statistically associated gene expression levels. However, a comprehensive, searchable resource integrating eQTMs across diverse tissues and disease contexts has been lacking. RESULTS: We developed the eQTM Atlas, a web-based resource that manually curates more than 11 million DNAm-gene expression associations from eight cohorts, covering 11 tissue types, four broad disease contexts, 173,886 unique CpG probes and 20,231 unique genes. The Atlas supports gene- or CpG- searches by tissue or disease type and finding associated CpG or genes, visualization of cis- and trans-eQTMs through genome browser, heatmap interfaces across various tissues, and cohort-level data downloads. By integrating eQTM results with EWAS resources, the eQTM Atlas enables users to connect disease- or trait-associated CpGs to statistically associated genes rather than relying solely on proximity-based gene annotation, supporting functional interpretation of EWAS findings and generation of disease-specific regulatory hypotheses. AVAILABILITY AND IMPLEMENTATION: The eQTM Atlas is freely available at https://shiny.crc.pitt.edu/eqtm_browser/. The web interface is implemented in R Shiny and hosted through the University of Pittsburgh Center for Research Computing (CRC). Source code is available at https://github.com/ads303/eQTM-Atlas.

DNA methylation↗

PubMed2026

Functional Prediction of Epitranscriptome.

N6-methyladenosine (m6A) is one of the most prevalent and well-studied RNA modifications, playing a pivotal role in many biological processes. With the recent advances in high-throughput sequencing technologies, tens of thousands of m6A sites have been reported. However, not all m6A sites are important or functionally significant, highlighting the need to distinguish biologically relevant m6As from non-functional or technically artefactual ones. Here, we describe ConsRM, which is a web-based resource that was designed to evaluate the importance of m6As from an evolutionary perspective. It introduced a novel scoring framework for quantifying the conservation degree of m6As in humans. Its web interface includes a database of 177998 distinct human m6A sites along with their calculated conservation score, and allows users to analyze their own data via the web server. ConsRM is freely accessible at: http://180.208.58.19/conservation/browser.html .

Humans↗

PubMed2026

A full review of online education resources available on antifungal stewardship.

BACKGROUND AND OBJECTIVES: Antifungal resistance represents an increasing global threat, driven by the rising burden of fungal disease. Antifungal stewardship (AFS) is a critical component of broader antimicrobial resistance (AMR) efforts, but education in this area remains less established than antibacterial stewardship initiatives. The scope and characteristics of the current landscape of online AFS resources have not yet been systematically described. To identify and evaluate online educational resources focused on fungal disease management and AFS, and assess their accessibility, format, educational design and implementation focus. METHODS: A structured search of internet search engines, distribution platforms and organizational websites was conducted to identify English-language web-based resources related to fungal disease management and stewardship. Resources were evaluated using predefined criteria including access model, format, length, educational design, interactivity and AFS content. An overall educational value score (1-10) was assigned. RESULTS: Twenty-three educational resources were identified. Most were delivered as online unfacilitated courses (11, 48%) and were short (<4 h) (12, 52%). Most focused on guidelines and syndromic management (18, 78%) and targeted doctors and/or nurses/midwives (22, 96%). Limited interactivity was reported in nine (39%) courses. Five courses (22%) had either a substantial or comprehensive focus on AFS. CONCLUSIONS: Online AFS educational resources are available and support awareness and knowledge development. However, they remain relatively few in number. Greater emphasis on implementation-focused learning, behaviour change components and broader global representation may enhance their impact.

Journal Article↗

PubMed2026

Deciphering differential mRNA and lncRNA expression profiles in response to PEG simulated drought stress in cucumber (Cucumis sativus L.).

Cucumber (Cucumis sativus L.), a vital fruit vegetable of the Cucurbitaceae family, originated in India ∼ 3000 years ago. It is widely used in the culinary, therapeutic, and cosmetic sectors. Cucumber cultivation is significantly impacted by drought stress, especially in arid and semi-arid regions. This study investigates the molecular response to drought using two contrasting cucumber lines: WBC-23-2 (drought-tolerant) and DGPC-59 (drought-sensitive). Drought was simulated using polyethylene glycol (PEG), and effects on physiological and biochemical traits were evaluated. The tolerant line exhibited reduced leaf wilting and higher relative water content (RWC). Based on these physiological markers, transcriptomic profiling was employed to identify the underlying regulatory networks. Analysis identified 4,736 DEGs, suggesting that the tolerant line's superior resilience is driven by preferential activation of genes involved in photosynthesis and glutathione metabolism. Conversely, the sensitive genotype showed enrichment in organonitrogen compound catabolism and water deprivation response. This divergence is further reflected in the regulation of 155 transcription factors (TFs) across various families, indicating distinct regulatory architectures between the two lines. Additionally, 774 drought-responsive long non-coding RNAs (lncRNAs) were identified, acting via cis, trans, and competing endogenous RNA (ceRNA) mechanisms to modulate gene expression. Key candidate genes associated with drought tolerance included WAT1-related protein At5g64700, thaumatin-like protein, berberine bridge enzyme-like 18, probable WRKY transcription factor, and pathogenesis-related protein 1. This study reveals a complex regulatory network of mRNAs, lncRNAs, and TFs underlying drought response and provides a valuable foundation for breeding drought-resilient cucumber cultivars. A web-based genomic resource, CsDTDb, has been developed and made publicly available to facilitate future functional genomics studies related to drought tolerance in cucumber.

DEGs↗

PubMed2026

DORSSAA: Drug-Target interactOmics Resource Based on Stability/Solubility Alteration Assay.

Advancements in high-throughput techniques such as Thermal Proteome Profiling and the high-throughput Proteome Integral Solubility Alteration assay have revolutionized our understanding of drug-protein interactions. Despite these innovations, the absence of an integrative platform for cross-study analysis of stability and solubility alteration data represents a significant bottleneck. To address this gap, we introduce Drug-target interactOmics Resource based on Stability/Solubility Alteration Assay (DORSSAA), an interactive and expandable web-based platform for the systematic analysis and visualization of proteome stability and solubility alteration assay datasets. Currently, DORSSAA features 1,135,985 records spanning 38 cell lines and organisms, 135 compounds, and 40,742 protein targets. Through its user-friendly interface, the resource supports comparative drug-protein interaction analysis and facilitates the discovery of actionable therapeutic targets. Through two case studies, methotrexate target profiling in A549 cells and combinatorial-therapy drug-target interactions in leukemia cell lines, we demonstrate DORSSAA's utility for identifying protein-drug interactions across diverse experimental contexts. This resource empowers researchers to accelerate drug discovery and enhance our understanding of protein behavior. Compared with data repositories and interaction databases, DORSSAA provides direct protein-level evidence of mechanisms of action with strict statistical control for each study. This enables more reliable identification of drug targets, off-target effects, and potential drug combinations.

Humans↗

PubMed2017

Functional mapping and annotation of genetic associations with FUMA.

A main challenge in genome-wide association studies (GWAS) is to pinpoint possible causal variants. Results from GWAS typically do not directly translate into causal variants because the majority of hits are in non-coding or intergenic regions, and the presence of linkage disequilibrium leads to effects being statistically spread out across multiple variants. Post-GWAS annotation facilitates the selection of most likely causal variant(s). Multiple resources are available for post-GWAS annotation, yet these can be time consuming and do not provide integrated visual aids for data interpretation. We, therefore, develop FUMA: an integrative web-based platform using information from multiple biological resources to facilitate functional annotation of GWAS results, gene prioritization and interactive visualization. FUMA accommodates positional, expression quantitative trait loci (eQTL) and chromatin interaction mappings, and provides gene-based, pathway and tissue enrichment results. FUMA results directly aid in generating hypotheses that are testable in functional experiments aimed at proving causal relations.

Chromatin↗

PubMed2024

TFinder: A Python Web Tool for Predicting Transcription Factor Binding Sites.

Transcription is a key cell process that consists of synthesizing several copies of RNA from a gene DNA sequence. This process is highly regulated and closely linked to the ability of transcription factors to bind specifically to DNA. TFinder is an easy-to-use Python web portal allowing the identification of Individual Motifs (IM) such as Transcription Factor Binding Sites (TFBS). Using the NCBI API, TFinder extracts either promoter or gene terminal regulatory regions, through a simple query of NCBI gene name or ID. It enables simultaneous analysis across five different species for an unlimited number of genes. TFinder searches for Individual Motifs in different formats, including IUPAC codes and JASPAR entries. Moreover, TFinder also allows de novo generations of a Position Weight Matrix (PWM) and the use of already established PWM. Finally, the data are provided in a tabular and a graph format showing the relevance and the P-value of the Individual Motifs found as well as their location relative to the Transcription Start Site (TSS) or the terminal region of the gene. The results are then sent by email to users facilitating the subsequent data analysis and sharing. TFinder is written in Python and freely available on GitHub under the MIT license: https://github.com/Jumitti/TFinder. It can be accessed as a web application implemented in Streamlit at https://tfinder-ipmc.streamlit.app. Resources are available on Streamlit "Resources" tab. TFINDER strength is that it relies on an all-in-one intuitive tool allowing users inexperienced with bioinformatics tools to retrieve gene regulatory regions sequences in multiple species and to search for individual motifs in a huge number of genes.

Transcription Factors↗

PubMed2004

WormBase as an integrated platform for the C. elegans ORFeome.

The ORFeome project has validated and corrected a large number of predicted gene models in the nematode C. elegans, and has provided an enormous resource for proteome-scale studies. To make the resource useful to the research and teaching community, it needs to be integrated with other large-scale data sets, including the C. elegans genome, cell lineage, neurological wiring diagram, transcriptome, and gene expression map. This integration is also critical because the ORFeome data sets, like other 'omics' data sets, have significant false-positive and false-negative rates, and comparison to related data is necessary to make confidence judgments in any given data point. WormBase, the central data repository for information about C. elegans and related nematodes, provides such a platform for integration. In this report, we will describe how C. elegans ORFeome data are deposited in the database, how they are used to correct gene models, how they are integrated and displayed in the context of other data sets at the WormBase Web site, and how WormBase establishes connection with the reagent-based resources at the ORFeome project Web site.

Animals↗

PubMed2026

Published Database Resources for Traditional, Complementary, and Integrative Medicine: Update of a Systematic Review.

BACKGROUND: Traditional, Complementary, and Integrative Medicine (TCIM) has been established in the academic context of universities. In recent years, strategies have been developed worldwide to strengthen the role of TCIM in supporting the health of the population. Online databases are a common way for obtaining evidence-based information. This article is an update of a former systematic review from 2010 on published databases resources for TCIM. METHODS: The databases CINAHL, CAMbase, Web of Science, MEDLINE/PubMed, and Google Scholar search engine were searched for databases related to TCIM published in peer-reviewed journals between 2010 and November 2024. All included databases were visited online, and information on the origin, content, and scope of the database was extracted. RESULTS: A total of 6579 articles were identified through the literature search. After exclusion of irrelevant articles, full-text screening of 127 articles yielded 37 new databases. Together with 16 still available old databases, these mainly contained information on herbal therapies (n = 15) and Traditional Chinese Medicine (n = 11) from 18 different countries. Newly identified medicinal plant databases offer various scientific resources such as crude drugs, indigenous plants, and structures for natural and phytochemical components with molecular biological content. CONCLUSIONS: This literature review illustrates the dynamic development in the database landscape over the last 15 years. While the number of bibliographic databases is shrinking, databases in the field of medical plants/herbal therapy content are on the rise, which might be due to advances in plant genomics and molecular biology.

Humans↗

PubMed2026

CancerOmicsStudio (CoS): a web server for integrative and interpretable analysis of multi-omics cancer data.

MOTIVATION: Large-scale omics resources, including The Cancer Genome Atlas, Genomics of Drug Sensitivity in Cancer, and the Cancer Dependency Map, have become essential for cancer research. However, these datasets are distributed across different platforms, formats and analysis frameworks, which limits their practical use by researchers without extensive computational expertise. RESULTS: We developed CancerOmicsStudio (CoS), a web server for integrative and interpretable analysis of multi-omics cancer data across 33 cancer types. CoS provides five major modules: CosAI, Traditional Analysis, Drug Sensitivity, CRISPR Dependency and Single-Cell Tumor Microenvironment. The Traditional Analysis module supports expression comparison, diagnostic evaluation, survival analysis, enrichment analysis and gene correlation. The Drug Sensitivity and CRISPR Dependency modules enable systematic evaluation of gene-drug response associations and gene essentiality in cancer cell lines. The Single-Cell Tumor Microenvironment module supports tumor microenvironment analysis at single-cell resolution. In total, approximately 1.23 million results have been precomputed to enable rapid retrieval. CosAI further allows users to submit natural-language queries and obtain results through a Real-time Analysis as Retrieval framework, with responses summarized by a lightweight language model. AVAILABILITY AND IMPLEMENTATION: CancerOmicsStudio is freely available at Zenodo (doi: 10.5281/zenodo.18744990) and https://cos.wanglab.bio.

Humans↗

PubMed2026

circASbase: A Comprehensive Database of Alternative Splicing Events in circRNAs.

Although extensive evidence has underscored the critical role of alternative splicing (AS) in generating mature circular RNA (circRNA) isoforms and augmenting their functional diversity, a significant gap remains in the availability of specialized databases housing circRNA AS events. To bridge this gap, we develop circASbase, a pioneering and comprehensive database that catalogs 452,129 AS events in 884,047 full-length circRNAs from 581 samples across 13 species, and provides rich annotations to facilitate understanding the splicing regulation of circRNA. Our findings reveal substantial differences between circRNAs and linear transcripts regarding the distribution and occurrence of AS events, highlighting the unique regulatory landscape of circRNAs. These special splicing events result in functional differences of circRNAs by affecting internal ribosome entry sites, N6-methyladenosine sites, open reading frames, protein features, microRNA targets, and more. In summary, circASbase not only meets the urgent need of the research community for data repositories, but also represents a significant advancement in our understanding of circRNA biology. With its user-friendly interfaces and web-based visualization tools, circASbase is poised to become an indispensable resource for researchers exploring the regulatory mechanisms and functional roles of AS events in circRNAs. This database will continuously drive new insights and discoveries in the field, setting the stage for further advancements in circRNA research. circASbase is freely available at http://reprod.njmu.edu.cn/cgi-bin/circASbase/.

Alternative Splicing↗

PubMed2026

Prevalence and risk factors of red blood cell alloimmunization among sickle cell disease patients in resource-limited countries: A systematic review and meta-analysis.

BACKGROUND: Sickle cell disease (SCD) is an inherited hemoglobinopathy characterized by hemoglobin S production, in which homozygous individuals (HbSS) develop a broad range of acute and chronic complications. While disease-modifying and curative therapies are increasingly available in high-income settings, red blood cell (RBC) transfusion remains the mainstay of treatment in resource-limited countries and is associated with high rates of alloimmunization. This systematic review and meta-analysis aimed to estimate the prevalence of alloimmunization and identify associated risk factors among patients with SCD living in resource-limited settings. METHODS: Africa Journals Online (AJOL), Embase, PubMed, Scopus, and Web of Science were searched for original studies published from inception to December 15, 2025. Only studies conducted in low- and lower-middle-income countries (LMICs) were included. Eligible studies evaluated the prevalence of alloimmunization in patients with SCD receiving RBC transfusions. A random-effects meta-analysis of proportions was performed to pool quantitative data, while qualitative findings were systematically summarized in tabular form. Statistical heterogeneity was assessed using the I² statistic and further explored using Baujat plots, leave-one-out analyses, and meta-regression. RESULTS: Our analysis included 27 studies conducted in Africa (n = 23) and Asia (n = 4), predominantly from lower-middle-income countries (n = 19) and mainly employing a cross-sectional design (n = 20), comprising 3128 previously transfused patients with SCD. The pooled prevalence of RBC alloimmunization was 8.76% (95% CI: 6.71-11.37%; I² = 75%). Higher alloimmunization rates were observed in West and North Africa, particularly in Côte d'Ivoire, Egypt, and Nigeria, whereas lower rates were reported in Asia and East Africa. The most frequently identified antibodies belonged to the Rh blood group system (n = 153), followed by the Kell system (n = 65). CONCLUSION: In resource-limited settings, RBC alloimmunization is a frequent and clinically significant complication in patients with SCD, contributing to increased morbidity and potential mortality. Targeted and economically viable antigen matching may reduce alloimmunization rates and improve transfusion safety in LMICs.

Humans↗

PubMed2024

Haplotype-resolved genome assembly and implementation of VitExpress, an open interactive transcriptomic platform for grapevine.

Haplotype-resolved genome assemblies were produced for Chasselas and Ugni Blanc, two heterozygous Vitis vinifera cultivars by combining high-fidelity long-read sequencing and high-throughput chromosome conformation capture (Hi-C). The telomere-to-telomere full coverage of the chromosomes allowed us to assemble separately the two haplo-genomes of both cultivars and revealed structural variations between the two haplotypes of a given cultivar. The deletions/insertions, inversions, translocations, and duplications provide insight into the evolutionary history and parental relationship among grape varieties. Integration of de novo single long-read sequencing of full-length transcript isoforms (Iso-Seq) yielded a highly improved genome annotation. Given its higher contiguity, and the robustness of the IsoSeq-based annotation, the Chasselas assembly meets the standard to become the annotated reference genome for V. vinifera. Building on these resources, we developed VitExpress, an open interactive transcriptomic platform, that provides a genome browser and integrated web tools for expression profiling, and a set of statistical tools (StatTools) for the identification of highly correlated genes. Implementation of the correlation finder tool for MybA1, a major regulator of the anthocyanin pathway, identified candidate genes associated with anthocyanin metabolism, whose expression patterns were experimentally validated as discriminating between black and white grapes. These resources and innovative tools for mining genome-related data are anticipated to foster advances in several areas of grapevine research.

Vitis↗

PubMed2025

Evaluating 12 automated, whole-genome sequencing analysis pipelines for Mycobacterium tuberculosis complex: a comparative study.

BACKGROUND: Reliance on complex, custom-built bioinformatics pipelines is a barrier to the implementation of whole-genome sequencing (WGS) of Mycobacterium tuberculosis in high-burden settings in some low-income and middle-income countries (LMICs). Automated analysis pipelines could address this inequity in access to WGS-based diagnostics and surveillance. This study aimed to systematically evaluate the performance and usability of publicly available WGS pipelines for M tuberculosis. METHODS: We identified automated M tuberculosis WGS analysis pipelines through searches of PubMed and GitHub from database inception up to Aug 31, 2024. Accuracy, cost, accessibility, and scalability were assessed for each pipeline. We evaluated the accuracy of genotypic drug susceptibility testing (gDST) using publicly available sequences with phenotypic susceptibility data for 12 antituberculosis drugs. We estimated pooled sensitivity and specificity for each pipeline, across all drugs, by conducting a bivariate meta-analysis, with random effects representing between-drug variability. Lineage classifications were compared, and a previously epidemiologically well-characterised dataset was used to compare measures of genomic relatedness. FINDINGS: Among 28 candidate pipelines, 16 were excluded as they were unmaintained and inexecutable. 12 pipelines (11 compatible with Illumina and four compatible with Nanopore), all free to use, were included for evaluation. Six pipelines processed and stored data remotely, but for five of these six, scalability was limited by the need to upload sequences through web portals. For local processing pipelines, scalability was dependent on substantial local computational resources, data storage capacity, and command-line interfaces that limited user-friendliness. Only one of six remote-processing pipelines removed human DNA sequences before server upload. gDST was similarly accurate across ten of 11 Illumina-compatible pipelines and three of four Nanopore-compatible pipelines. All pipelines classified the main lineages consistently, although there were differences at sublineage resolution. Outputs from three of four pipelines reporting genomic relatedness were compatible with commonly cited single nucleotide polymorphism difference thresholds. INTERPRETATION: Numerous automated analysis pipelines capable of enhancing equity in M tuberculosis WGS are available. Given the overall similarities between the pipelines evaluated in this study in terms of gDST performance, lineage classification, and genomic relatedness inference, non-functional attributes such as availability, accessibility, scalability, and privacy could represent the point of difference for prospective users in LMICs with a high burden of tuberculosis. FUNDING: The Rhodes Trust, Wellcome, Ellison Institute of Technology, and the UK National Institute for Health and Care Research Oxford Biomedical Research Centre.

Mycobacterium tuberculosis↗

PubMed2026

The Gabriella Miller Kids First Data Resource for genomic research in pediatric cancer and congenital anomalies.

Nine-year-old brain tumor patient Gabriella Miller challenged members of Congress to "stop talking and start doing" when providing federal funding for research into cures for pediatric cancer and congenital anomalies. Though she ultimately lost her life to that cancer, her advocacy efforts resulted in the 2014 Gabriella Miller Kids First Research Act, launching the Gabriella Miller Kids First Pediatric Research Program at the National Institutes of Health (NIH). The overarching goal of the Gabriella Miller Kids First Pediatric Research Program is to help researchers uncover new insights into the biology of childhood cancer and congenital anomalies. Following the signing of the Gabriella Miller Kids First Research Act 2.0 in January 2025, the program has been extended at NIH through 2028 to advance the groundwork laid in the program's first ten years. The Gabriella Miller Kids First Data Resource Center has since honored her legacy by building a comprehensive data resource for genomic research into pediatric conditions. Data from more than 30,000 participants annotated with demographic and clinical information related to their diagnoses have been released for secondary research and analysis using the center's web-based platforms. This paper analyzes the outcomes of the initiative and highlights breakthroughs made by the larger research community resulting from the availability of this data resource. We explore the future expansion of the data resource to include new modalities and tools for supporting life-saving research for children like Gabriella Miller.

Humans↗

PubMed2026

Searching the druggable genome using large language models.

SUMMARY: The druggable genome encompasses the genes that are known or predicted to interact with drugs. The Drug-Gene Interaction Database (DGIdb) provides an integrated resource for discovering and contextualizing these interactions, supporting a broad range of research and clinical applications. DGIdb is currently accessed through structured web interfaces and API calls, requiring users to translate natural-language questions into database-specific query patterns. To allow for the use of DGIdb through natural language, we developed the DGIdb Model Context Protocol (MCP) server, which allows large language models (LLMs) access to up-to-date information through the DGIdb API. We demonstrate that the MCP server improves an LLM's ability to answer questions requiring accurate, up-to-date biomedical knowledge drawn from structured external resources. AVAILABILITY AND IMPLEMENTATION: The DGIdb MCP server is detailed at https://github.com/dgidb/dgidb-mcp-server and includes instructions for accessing the server through the Claude desktop app.

Large Language Models↗

PubMed2026

Searching the Druggable Genome using Large Language Models.

SUMMARY: The druggable genome encompasses the genes that are known or predicted to interact with drugs. The Drug-Gene Interaction Database (DGIdb) provides an integrated resource for discovering and contextualizing these interactions, supporting a broad range of research and clinical applications. DGIdb is currently accessed through structured web interfaces and API calls, requiring users to translate natural-language questions into database-specific query patterns. To allow for the use of DGIdb through natural language, we developed the DGIdb Model Context Protocol (MCP) server, which allows large language models (LLMs) access to up-to-date information through the DGIdb API. We demonstrate that the MCP server greatly enhances an LLM's ability to answer questions requiring accurate, up-to-date biomedical knowledge drawn from structured external resources. AVAILABILITY AND IMPLEMENTATION: The DGIdb MCP server is detailed at https://github.com/griffithlab/dgidb-mcp-server and includes instructions for accessing the server through the Claude desktop app.

Journal Article↗