Abstract
The 2026 Nucleic Acids Research database issue has 182 papers from across biology and neighbouring fields. Eighty-four of these papers describe new databases, while 86 are updates on databases that have previously appeared here. Twelve more papers cover databases most recently published elsewhere. New nucleic acid databases include NapRNAdb for noncapped RNA and GlycoRNAdb. Protein structure is covered by updates from wwPDB members and the AlphaFold Database; SMART, PROSITE, and eggNOG cover domains and families. The Open Enzyme Database and QSproteome are new community-orientated initiatives. JoGo covers hierarchically named and contextualised human haplotypes in the issue’s first Breakthrough paper; So3D provides genuinely 3D spatial transcriptomics in the other. Foundational databases Genenames.org and Gene Ontology also provide updates. The Database Issue is freely available on the Nucleic Acids Research website (https://academic.oup.com/nar). At the NAR online Molecular Biology Database Collection (http://www.oxfordjournals.org/nar/database/c/), over the past year, 899 entries were reviewed, 96 new resources added, and 319 discontinued URLs removed, bringing the total number of databases to 2173.
New and updated databases
The 33rd Nucleic Acids Research database issue contains 182 papers spanning biology and related areas. The issue features 84 papers describing new databases (Table 1) as well as 12 on databases most recently published elsewhere (Table 2). There are also 86 papers on resources that have previously appeared here. As usual, the issue leads with updates from the major database providers at the European Bioinformatics Institute (EBI), the U.S. National Center for Biotechnology Information (NCBI), and the National Genomics Data Center (NGDC) in China [1–3]. Notably, the last of these now includes the aptly named BIG search, which scans across databases not just of the NGDC and partners, but also from the EBI and NCBI. The usual categorization of remaining papers then follows: (i) nucleic acid sequence and structure, transcriptional regulation; (ii) protein sequence and structure, proteomics; (iii) metabolic and signalling pathways, enzymes and networks; (iv) genomics of viruses, bacteria, protozoa, and fungi; (v) genomics of human and model organisms plus comparative genomics; (vi) human genomic variation, diseases, and drugs; (vii) plants; and (viii) other topics. As always, many databases span multiple categories, so readers are encouraged to browse the whole issue.
Table 1.
Descriptions of new databases in the 2026 NAR database issue
| Database Name | URL | Short description |
|---|---|---|
| AMRnet | https://www.amrnet.org/ | Genome-derived AMR surveillance data |
| ANPDB | https://african-compounds.org | African Natural Products Database |
| ARKbase | https://datascience.imtech.res.in/anshu/arkbase/ | Antimicrobial Resistance Knowledgebase |
| ASTRA | https://astra-db.com/ | The Atlas of STress Response Activity |
| CCCdb | http://www.licpathway.net/cccdb/index.php | Cell-cell communication in human and mouse |
| CellSNVReg | http://bio-bigdata.hrbmu.edu.cn/CellSNVReg/index.jsp | SNV-mediated regulatory perturbations in single-cell and spatial omics |
| ChickenGTEx Atlas | http://chicken.farmgtex.org | Chicken genotypes and phenotypes |
| ChromPolymerDB | https://chrompolymerdb.bme.uic.edu/ | Single-Cell 3D Chromatin Structures |
| CircTarget | https://circtarget.cn | circRNA-target RNA interactions |
| ClinMAVE | https://ngdc.cncb.ac.cn/clinmave/ | Clinical application of MAVE assays |
| CNAScope | https://cna.fengslab.com/ | Pan-Cancer Copy Number Variation Database |
| CRESTA | https://cresta.renlab.cn/ | Cellular response to external stressors transcriptome atlas |
| dbCAN-HGM | https://pro.unl.edu/dbCAN_HGM | CAZymes and gene clusters in human gut microbiomes |
| DeepSpaceDB | https://www.deepspacedb.com | Curated and interactive database of spatial transcriptomics |
| DisCP-Atlas | http://www.discpatlas.net | GWAS and single cell data link cellular processes to disease [CHECK] |
| DOO | https://DeepOceanOmics.org | Deep Ocean Omics |
| DynaRepo | https://dynarepo.inria.fr/ | Macromolecular conformational dynamics |
| enhancer3D | https://3dgnome.mini.pw.edu.pl/enhancer3D/ | Chromatin 3D Structure Database for Archaic and Modern Humans |
| ENSURE | https://trna.lumoxuan.cn/ | Encyclopedia of Suppressor tRNA |
| EnzEngDB | http://enzengdb.org/ | Enzyme Engineering Database |
| GEAR | https://scientist.xsrv.jp/ | Diurnal and circadian gene expression in Arabidopsis |
| GENEasso | https://www.geneasso.net | Disease-Gene Associations GWAS by diverse methods |
| GeneFamily | https://gh.deepomics.org/ | Mammalian gene family database |
| gutMSNP | https://bio-computing.hrbmu.edu.cn/gutMSNP/home | SNPs in the human gut microbiome |
| GlycoRNAdb | http://www.glycornadb.com | GlycoRNA |
| HapScoreDB | https://bcglab.cibio.unitn.it/hapscoredb | Haplotype-resolved protein-coding sequences and pLM fitness scores |
| HLRMDB | http://www.inbirg.com/hlrmdb/ | Human long-read metagenomic database |
| Human-scATAC-Corpus | https://health.tsinghua.edu.cn/human-scatac-corpus/ | Human scATAC-seq data |
| iFish | https://gonglab.hzau.edu.cn/iFish | Fish multi-omics |
| IGVF Catalog | https://api.catalog.igvf.org/ | Impact of Genomic Variation on Function Catalog |
| Iridovirus Comprehensive Database | https://www.iridovirus.com/ | Iridovirus sequences, epidemiology and disease management |
| JoGo | https://jogo.csml.org | Haplotype annotation for canonical human protein-coding genes |
| KnockRBP | https://knockrbp.xu-bioinfo.com | Multi-omics of RNA-binding protein knockout or knockdown |
| m6AConquer | http://rnamd.org/m6aconquer | Consistent Quantification of m6A RNA Modification Data |
| MacrocycleDB | https://macro-db.dpbio.tech/ and https://macro-db.cn/ | Macrocycle compounds |
| MeDIC | https://medic.renci.org/ | Medicines, Diseases, and Indications |
| MediaAssist | https://mediaassist.ncl.res.in | Serum-free cell culture media information |
| Meta-VR | https://www.meta-virome.org/ | Metagenome-derived viruses |
| MetabFlow | https://bddg.hznu.edu.cn/metabflow/ | Natural product metabolism |
| metagRoot | https://pavlopoulos-lab.org/metagroot/ or https://www.metagroot.org | Protein Families Associated with Plant Root Microbiomes |
| Metalog | https://metalog.embl.de/ | Manually annotated metadata for metagenomic data |
| MetaTraits | https://metatraits.embl.de | Microbial phenotypic traits |
| MGDB | http://mgdb.idruglab.cn/ | Molecular Glues |
| MGTbind | https://mgtbind.pkumdl.cn | Molecular Glue and Ternary binding Database |
| MicroAgroBiome | https://agrobiom.matmor.unam.mx | Metagenome-assembled genomes from crop-associated environments |
| MicrobialScope | https://microbial.deepomics.org/ | Richly annotated genomes from bacteria, archaea, fungi, and viruses |
| MITE | https://mite.bioinformatics.nl/ | Minimum Information about a Tailoring Enzyme Database |
| MolGlueDB | https://www.molgluedb.com | Molecular Glues |
| MouseOmics | http://www.varnatech.cn/MouseOmics | Mouse multi-omics |
| NapRNAdb | https://bioinformaticsscience.cn/naprnadb | Noncapped RNAs (napRNAs) |
| Ocean-M | https://om.biocloud.net | Multi-omics database of marine microbiomes |
| OED | https://openenzymedb.platform.moleculemaker.org/ | Open Enzyme Database |
| PBMCpedia | https://web.ccb.uni-saarland.de/pbmcpedia/ | Human peripheral blood mononuclear cell transcriptomics |
| pcsRNADB | http://pcsrnadb.cloudna.cn/#/Home | pan-cancer small RNA expression |
| PersADE | https://47.88.56.212/PersADE/ | Personalised adverse drug events |
| PMADS | https://pmads-db.org | PTM–drug–disease relationships |
| PRIME | https://primedb.sjtu.edu.cn | Phenotypic Reference for Integrated Microbiome Enrichment |
| ProteoNexus | https://www.proteonexus.com/ | The plasma proteome mediating complex disease |
| QSproteome | https://QSProteome.org | Computationally predicted oligomeric protein complexes |
| RaCE | https://biospace.shinyapps.io/race/ | Rare Cancer Explorer |
| RadioPharm | https://idrblab.org/radiopharm/ | Radiopharmaceuticals |
| ResMicroDb | https://resmicrodb.cncb.ac.cn | The respiratory microbiome in health and disease |
| Ribocentre-aptamers | https://aptamer.ribocentre.org/ | RNA aptamers |
| RMpore | https://rmpore.renlab.cn/ | Single-molecule RNA modification profiling via Nanopore sequencing |
| RNApaceDB | http://43.163.194.16/RNAPaceDB/ | RNA velocities |
| scBrainScope | http://www.brainscopes.org or http://8.142.154.29/scBrainScope/ | Cross-species multi-dimensional integrated brain atlas |
| scCT-DB | http://scctdb.ncpsb.org.cn | Cancer patient-derived paired pre- and post-treatment single-cell transcriptomes |
| scGeneBank | http://8.142.154.29/scGeneBank or http://www.genebank.info | Cross-species screening of functional gene sets at single-cell resolution |
| scMOVIR | https://pgx.zju.edu.cn/scmovir | Single-cell multi-omics database for viral infections and immune responses |
| scVMAP | https://bio.liclab.net/scvmap/ | Single-cell chromatin accessibility data and causal variants |
| SDMap | http://bio-bigdata.hrbmu.edu.cn/SDMap/ | Spatial Drug perturbation Map |
| SeekPCMdb | https://ngdc.cncb.ac.cn/seekpcmdb/ | Protein-coding mutations in human diseases |
| smallBARNA | https://web.ccb.unisaarland.de/smallbarna/ | Curated kingdom-wide bacterial sRNA |
| So3D | http://bio-bigdata.hrbmu.edu.cn/So3D or https://so3d.bio-database.com/ | 3D spatial omics |
| Spatial2GWAS | http://www.spatial2gwas.cn | Spatial transcriptomic regions linked to GWAS traits |
| Spatial GWAS Atlas | https://zhaolab.cpl.ac.cn/spatialgwas | Spatial transcriptomic regions linked to GWAS traits |
| SVAtlas | https://www.svatlas.org/ | Single extracellular vesicle omics resource |
| TE-SCALE | https://ngdc.cncb.ac.cn/te-scale/ | Transposable Element Single-Cell Analysis Landscape |
| TEDD | https://ngdc.cncb.ac.cn/tedd | Translation Efficiency Dynamics Database |
| theRNA | https://therna.renlab.cn/ | Therapeutic RNA |
| TPDdb | https://idrblab.org/TPDdb/ | Targeted Protein Degraders |
| TTDB | https://sysbio.gzzoc.com/ttdb/index.html | Transcriptome Turnover Database |
| VIRE | https://vire.embl.de | Viral Integrated Resource across Ecosystems |
| VirJenDB | https://www.virjendb.org | Virus genomics |
Table 2.
Updated descriptions of databases most recently published elsewhere
| Database Name | URL | Short description |
|---|---|---|
| 3D Genome Browser | https://3dgenome.fsm.northwestern.edu | 3D Genome Architecture |
| CD-CODE | https://new.cd-code.org | Biomolecular condensates and their constituents |
| CIRCpedia | https://bits.fudan.edu.cn/circpediav3 | Circular RNAs across 20 species |
| CisBP-RNA | https://www.cisbp.org/rna/ | Eukaryotic RNA Binding Protein motifs |
| connectomeDB | https://connectomedb.org | Human ligand–receptor interactions |
| groovDB | https://groov.bio | Prokaryotic transcription factor biosensors and their properties |
| Massbank | https://massbank.jp/ | Mass Spectral Database |
| OmniPath | https://omnipathdb.org/ | Integrated molecular interactions, pathways, and biological annotations |
| PaxDb | https://www.pax-db.org/ | Protein abundance at organism and tissue levels |
| PRECOG and related resources | https://precog.stanford.edu | Gene-outcome associations across cancer |
| RegNetwork | http://www.zpliulab.cn/RegNetwork/home | Gene Regulatory Networks in human and mouse |
| riboCIRC | http://www.ribocirc.com | Translatable circRNAs |
In the ‘Nucleic acid databases’ section a number of interesting classes of RNA earn new bespoke databases: GlycoRNAdb [4] captures the expression, composition, and glycosylation sites of the recently discovered cell surface glycoRNA molecules, while aptamer structures and their diverse ligands are the focus of Ribocentre-aptamer [5]. Elsewhere, noncapped RNAs are catered for by NapRNAdb [6], which encompasses sequences, evolution, and expression of eight classes across 40 species; and bacterial sRNAs are covered by SmallBARNA [7], the content of which derives exclusively from 1000 carefully curated papers. Suppressor tRNAs, their natural occurrence and therapeutic potential, are the focus of the new ENSURE database [8]. It offers an AI-driven user query system, as many resources have introduced, and notably uses the latest AlphaFold 3 [9] to model RNA molecules. Circular RNAs are comprehensively covered by the new CircTarget [10], which captures RNA–RNA interactome data from several cross-linking methods and provides a rich context highlighting potential links to disease. This joins the returning CircleBase [11], which expands 12-fold and now covers mouse data for cross-species comparison, and two databases that are new to the issue: CIRCpedia [12], which adopts community recommendations on nomenclature and covers 20 species; and riboCIRC [13], for translatable circRNAs, which doubles in size, introduces new layers of evidence translation, and offers more comprehensive characterization of the encoded peptides. Also welcomed to the issue is CisBP-RNA [14], the popular resource for eukaryotic RNA-binding proteins and their motifs. Their update provides a helpful pipeline to assess the RNA-binding protein complement of a newly sequenced genome. Popular returning databases include RNAcentral [15], which reports two major developments—two AI tools to link literature to entries and provide summaries; and a shift in representation from sequences to genes and their transcripts. Elsewhere, NONCODE [16], the resource for long non-coding RNAs, adds transcriptomics data from millions of human single cells, and MODOMICS [17] celebrates 20 years by vastly expanding its RNA sequence content through curation of data from the Sci-ModoM database [18]. Finally, the hugely influential database of rRNA SILVA reappears [19] after a 12-year gap to report its new home alongside other important databases for biological classification [20, 21].
The protein section includes updates from two members of the wwPDB consortium [22]. The RCSB paper [23] has a detailed and fascinating report on its incorporation of integrative/hybrid models, i.e. those resulting from multiple experimental and computational methods; while PDBe [24] reports on new clean and stylish entry pages, the result of extensive user feedback, and the welcome facility for users to upload their own residue-level data to view in the context of PDB structures and annotations. The AlphaFold Protein Structure Database also has an update [25] describing a series of significant improvements: alignment to a more recent UniProt [26] release, coverage of isoforms, provision of multiple sequence alignments generated during model construction, and a neat, tabbed interface with integration of results from The Encyclopedia of Domains [27]. Elsewhere, DynaRepo [28] is a new database of molecular dynamics trajectories containing, collectively, over a millisecond of simulation across single proteins and protein complexes. Of course, not all proteins are structured, and the popular DisProt for intrinsically disordered proteins [29] reports how careful extrapolation across species can magnify disorder annotations by two orders of magnitude and illustrates the team’s committed engagement with users, ontologies, and community standards. The proteins underlying phase separation and condensate formation are covered by an updated PhaSepDB [30] that doubles in size as a result of an AI prioritization plus human curation approach, now becoming common; and by CD-CODE [31], appearing in the issue for the first time, that significantly expands to include nucleic acids, condensatopathies, small molecules associated with condensates, and condensates linked to infection. Among resources for domains and families, PROSITE returns [32] after a long hiatus to report better integration with other databases, use of AlphaFold models for domain definition, and some interesting case studies. Elsewhere, the SMART database [33] approaches 30 years with an update illustrating a redesigned user interface and emphasizing the rich context provided by other foundational databases, from STRING [34] to KEGG [35] to Gene Ontology [36]. The update from the popular database of orthology predictions eggNOG [37] describes how the latest version results from a quite different approach that produces groups with greater functional consistency, while the new database, GeneFamily [38], majors on high-quality analysis and visualization tools for diversity, evolution, and genomic context for 2000 mammalian gene families.
In the section for metabolism and signalling, enzymes are a particular focus. The well-established BRENDA reports new features such as gene search and pathway summaries [39], while the new Open Enzyme Database [40] aims to serve as a community repository for enzyme data, offering tools for prediction of kinetic constants and an interesting enzyme recommender based on chemoinformatics analysis of the target substrate. GotEnzymes focuses on predicted enzyme properties, now adding thermal parameters to kinetic constants [41]. Two other new enzyme databases are MITE [42], which offers expert-curated information on the tailoring enzymes that are central to secondary metabolite synthesis; and EnzEngDB [43], which covers enzyme engineering campaigns—users can not only deposit data, but also use helpful tools for visualization and analysis. Two well-established network databases contribute updates: Reactome [44] has a new interface with a range of appealing visualizations, including a clever new disease-versus-normal-state comparison, and an AI chatbot, while SIGNOR [45] showcases a new PhosphoSIGNOR section for phosphorylation-related signalling. They are joined by OmniPath [46], appearing in the issue for the first time, which integrates 168 resources and offers a variety of modes of interactive and programmatic access. Another database arriving in the issue is the foundational MassBank for mass spectral data in metabolomics and environmental chemistry [47]. Elsewhere, QSproteome [48] is a new database for computationally predicted oligomeric protein complexes that offers a user-friendly upload portal, a variety of visualizations and scores, and even a gamified workflow to help engage the community in re-curation efforts. Finally, there is significant expansion reported at FerrDb, a database initially focused specifically on ferroptosis, but which now expands hugely to cover 22 modalities of regulated cell death [49].
The next section covers viruses and microbes, and there are updates from two pillars of microbial taxonomy and systematics. GTDB [50] offers a comprehensive update, including a commitment to extend the current prokaryote-only database to fungi; while another update covers both TYGS and LPSN, which have expanded content, especially for cyanobacteria and medically important bacteria [20]. Another notable update covers the virus taxonomy defined by the ICTV: it details changes to computing infrastructure, improved visualisation tools, and efforts towards training and outreach [51]. Viruses in general are well-represented. For example, two databases cover human viral diseases: an update from ViMIC [52] reports a move from transcriptomics alone to multi-omics and includes two interesting case studies; while the new database scMOVIR [53] offers a single-cell and multi-omics perspective on viral infections and immune responses. Two more new databases focus on metagenome-assembled virus sequences: VIRE [54] links millions of virus genomes and their encoded functions to environments, and benefits from integration with the SPIRE database for metagenome-assembled genomes [55] and the Metalog resource for relevant manually curated metagenome metadata (also debuting in this issue [56]). MetaVR [57] is the successor to IMG/VR [58] and expands its content and diversity significantly, also adding information on eukaryotic hosts as well as AlphaFold-predicted protein structures. Antimicrobial resistance is covered by two new databases: ARKbase [59] is a multi-dimensional database created in response to the publication of the WHO Bacterial Priority Pathogen list, while AMRnet [60] provides comprehensive geographical and temporal visualization of public genomes, their variants and resistance properties. Finally, a number of databases cover the human microbiome. The latest update from GMrepo for the human gut microbiome describes how more abundant data and facilities for comparison between projects allow firmer conclusions on linkages between microbes and phenotypes [61]. Meanwhile, the new gutMSNP [62] focuses on single nucleotide polymorphisms in gut microbes, allowing them to be linked to phenotypes. Finally, another new resource, ResMicroDb [63], comprehensively covers the human respiratory microbiome and provides thousands of microbe-disease associations.
This year, the human, model organism, and comparative genomics section houses both the issue’s Breakthrough articles. The first, JoGo [64], uses long-read sequenced genomes from across the globe to define millions of haplotypes across MANE-standardized human genes [65]. Inspired by conventions for naming HLA alleles, the resource introduces a consistent hierarchical nomenclature, allowing numbering in accordance with global frequency. Links to other databases—ClinVar [66], GWAS Catalogue [67], and GTEx [68]—as well as haplotype-expression QTL results facilitate the identification of variants relevant to gene regulation, disease, and precision medicine. The second Breakthrough article is from So3D [69], a three-dimensional spatial genomics database. Outside a few specialized resources, current databases focus analysis within 2D slices, while So3D carries out analysis between slices in the third dimension. Data include 30 human datasets across 10 organs and multiple diseases, and 33 Drosophila datasets informing on development. A comprehensive range of analytical options includes identification of spatially differentially expressed genes, cell–cell communication, and integration of single-cell datasets to map cell types in 3D. Two other new arrivals, Spatial GWAS Atlas [70] and Spatial2GWAS [71], each link spatial transcriptomics regions to GWAS traits to help elucidate the spatial mechanisms behind complex traits, and thereby facilitate therapeutic target discovery and precision medicine. The 3D chromatin structures ultimately underlying transcriptional regulation are the focus of two databases: enhancer3D [72] interestingly covers ancient as well as modern humans and measures enhancer-promoter distances; while ChromPolymerDB [73] contains single-cell chromatin structures and thereby allows comparisons across cell types, developmental stages, and disease contexts. Elsewhere, two stalwarts of the genomics space, Ensembl and UCSC Genome Browser, each offer their usual annual update. Ensembl [74] reports addition of nearly 2000 new genomes, better treatment of human and barley pangenomes, and improved prediction of the impact of variants; while the Browser [75] has (like Ensembl) absorbed data from MaveDB [76] to guide variant interpretation and has a new tool to facilitate liftover of annotations from one assembly to another. Two major immunogenetics databases also have updates: IPD-IMGT/HLA [77] for HLA system alleles addresses rapid growth with new submission and retrieval tools; and IMGT [78] for immunoglobulins and T-cell receptors reports new presentation, analytical, and predictive tools. There is also an interesting pair of new aquatic databases: iFish [79] ranges widely across 88 species and captures an impressive array of omics data; while Deep Ocean Omics [80] targets the fascinating biology of that extreme environment, with multi-omics data for 68 species across seven phyla. Finally, Genenames.org [81] describes the interesting variety of routes by which official gene names are introduced or altered and showcases a whole new initiative on plant gene names.
In the section on human genomic variation, diseases, and drugs, there are several new interesting cancer databases: CNAScope [82] focuses on copy number aberrations and offers a wide variety of annotations and interactive visualization tools; while PCsRNAdb [83] looks at small ncRNAs in cancer, their (differential) expression, and targets. Elsewhere Rare Cancer Explorer [84] covers 13 unusual tumour types comprehensively, from gene expression to drug response; scCT-DB [85] provides paired scRNA-seq data from patients before and after drug treatment to address perturbation and resistance; and TE-SCALE [86] explores transposable element expression at single-cell resolution across human cancers. They are joined by updates from OncoDB [87], which adds new database modalities such as proteomics and chromatin accessibility, as well as sophisticated tools to explore cross-omics relationships; and, publishing here for the first time, PRECOG [88], which links gene expression to clinical outcome and where there is a new focus on paediatric cancer. Two databases explore human genome variation broadly: the popular FAVOR [89] reports substantial expansion of annotations, a genome browser, and an AI interface to assist the user with navigation and interpretation; while the new IGVF Catalogue [90] assembles diverse experimental and computational data into a vast graph database with three billion nodes. On drug targets, the new database GENEasso [91] helps discover disease-gene associations more reliably through the integration of different statistical models, and the popular Therapeutic Target Database [92] has valuable new data on, for example, the clinical profiles of approved drugs. The effects of protein post-translational modifications on drug sensitivity and resistance are captured by the new PMADS database [93], with thousands of curated links and many more computationally predicted from proteomics data. Drug transporters are covered by VARIDT [94], which now considers their distribution at tissue, cell, and subcellular levels; while mechanisms of drug resistance are dealt with by DRESIS [95], which includes new data on metabolic reprogramming and structural variation, and which contributes our striking cover image. Bridging targets and the drugs themselves is the venerable IUPHAR/BPS Guide to Pharmacology, which, among many improvements, has a new focus on antibacterial pharmacology [96]. Moving on to the drugs themselves, distinct classes of therapeutics gain their own databases: theRNA [97] covers therapeutic RNAs across nine major classes through curation of thousands of papers; while RadioPharm [98] covers the interestingly diverse array of radiopharmaceuticals; and Macrocycle-DB [99] is a specialized resource for the structure, bioactivity, and chemical properties of this important class. Finally, targeted protein degraders of six kinds are covered by TPDdb [100], while no fewer than three new databases capture developments in the specific area of molecular glues [101–103].
The plant database section contains two updates. The first, from Gramene [104], reports valuable new pan-genome subsites for four crops and numerous other improvements; while the Plant Genome Duplication Database [105] reports an eight-fold expansion and hence much better coverage of plant diversity. New databases include GEAR, for diurnal and circadian gene expression in Arabidopsis [106], and two new databases for microbes associated with plants. metagRoot [107] discovers protein families associated with plant root microbiomes, linking them to taxonomy, function, geography, and protein structure; while MicroAgroBiome [108] offers genomes derived from 500 metagenomic studies of the environments of 28 crops. The final section includes updates from two behemoths that defy easy pigeonholing in the previous sections. The Gene Ontology paper describes expansion of several focus areas, such as multi-organism interactions, alongside a new curated set of annotations for human genes, the ‘functionome’ [36]. ChEBI, for curated chemical entities of biological interest, reports a complete reengineering of its web presence in order to allow it to operate in a more automated and sustainable fashion [109]. And bench scientists will appreciate MediaAssist [110], which catalogues the components of serum-free media and co-dependencies, facilitating medium design and optimization.
Finally, a word on changing guidelines around database funding and submission to the database issue. The year has, sadly, seen some acute funding problems strike even major, well-established databases. For the very survival of these crucial resources, such situations may require abrupt shifts to new funding models and hence more restrictive control of access to database content. The database issue has hitherto required that all content of submitting resources be available in some form for free and without the need for users to register. Given the current issues in the sector, we are now introducing some flexibility in exceptional cases. In the future, contributing databases that are forced to charge users and introduce necessary user registration may still be invited to submit to the issue by prior agreement with the editor.
NAR online molecular biology database collection
As part of our ongoing commitment to maintaining the freely accessible NAR online Molecular Biology Database Collection (http://www.oxfordjournals.org/nar/database/c/), we have continued to monitor and curate the listed resources. During this comprehensive annual review, 899 entries were updated, 96 new resources were added to the database, and 319 outdated or discontinued entries were removed. Additional curation efforts, incorporating recent updates and user feedback, have brought the total number of databases in this release to 2173. We encourage authors to submit their updates to XMF at xose.m.fernandez@gmail.com in plain text, preferably using the template provided at http://www.oxfordjournals.org/nar/database/summary/1.
Acknowledgements
We thank Dr Martine Bernardes-Silva and Meera Solanki, especially, and the rest of the Oxford University Press team led by Rebecca Lane for their help in compiling this issue.
Contributor Information
Daniel J Rigden, Department of Biochemistry, Cell and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Crown Street, Liverpool L69 7ZB, United Kingdom.
Xosé M Fernández, IQVIA Ltd., The Point, 37 North Wharf Road, London W2 1AF, United Kingdom.
Conflict of interest
The authors' opinions do not necessarily reflect the views of their respective institutions.
Funding
Funding to pay the Open Access publication charges for this article was provided by Oxford University Press.
References
- 1. Sayers EW, Bolton EE, Fine AM et al. Database resources of the national center for biotechnology information in 2026. Nucleic Acids Res. 2025;gkaf1060. 10.1093/nar/gkaf1060. [DOI] [Google Scholar]
- 2. Thakur M, Bosc N, Brooksbank C et al. EMBL’s European bioinformatics institute (EMBL-EBI) in 2025. Nucleic Acids Res. 2025;gkaf1078. 10.1093/nar/gkaf1078. [DOI] [Google Scholar]
- 3. CNCB–NGDC Members and Partners . Database resources of the national genomics data center, China national center for bioinformation in 2026. Nucleic Acids Res. 2025;gkaf1172. 10.1093/nar/gkaf1172. [DOI] [Google Scholar]
- 4. Zheng C, Ao Y, Zhang Z et al. GlycoRNAdb: a database of glycoRNA sequences, structures, abundance, and glycan information across tissues and cell lines. Nucleic Acids Res. 2025;gkaf1246. 10.1093/nar/gkaf1246. [DOI] [Google Scholar]
- 5. Lu Z, Sun H, Fu B et al. Ribocentre-aptamer: an integrative, structure-focused database for RNA aptamers. Nucleic Acids Res. 2025;gkaf1016. 10.1093/nar/gkaf1016. [DOI] [Google Scholar]
- 6. Xuan J, Xiao C, Luo Y et al. NapRNAdb: a multispecies repository and analytical platform for napRNA discovery and functional annotation. Nucleic Acids Res. 2025;gkaf1100. 10.1093/nar/gkaf1100. [DOI] [Google Scholar]
- 7. Rishik S, Molano LAG, Khalid SM et al. SmallBARNA 2026: a kingdom-wide bacterial sRNA resource. Nucleic Acids Res. 2025; gkaf999. 10.1093/nar/gkaf999. [DOI] [Google Scholar]
- 8. Ouyang Z, Zhang Y, Feng F et al. ENSURE: the encyclopedia of suppressor tRNA with an AI assistant. Nucleic Acids Res. 2025;gkaf1062. 10.1093/nar/gkaf1062. [DOI] [Google Scholar]
- 9. Abramson J, Adler J, Dunger J et al. Accurate structure prediction of biomolecular interactions with AlphaFold 3. Nature. 2024;630:493–500. 10.1038/s41586-024-07487-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Zhang H, Zhang Y, Yuan Z et al. CircTarget: a comprehensive database of circRNA–target RNA interactions across multiple cell types. Nucleic Acids Res. 2025;gkaf1280. 10.1093/nar/gkaf1280. [DOI] [Google Scholar]
- 11. Wei L, Shi L, Wu N et al. CircleBase V2: an eccDNA annotation platform across cancers and species. Nucleic Acids Res. 2025;gkaf1266. 10.1093/nar/gkaf1266. [DOI] [Google Scholar]
- 12. Zhai SN, Zhang YY, Chen MH et al. CIRCpedia v3: an interactive database for circular RNA characterization and functional exploration. Nucleic Acids Res. 2025;gkaf1039. 10.1093/nar/gkaf1039. [DOI] [Google Scholar]
- 13. Xu Y, Yang L, Tang Y et al. riboCIRC v2.0: an expanded resource for translatable CircRNAs. Nucleic Acids Res. 2025;gkaf1022. 10.1093/nar/gkaf1022. [DOI] [Google Scholar]
- 14. Rosado-Tristani DA, Albu M, Chen X et al. CisBP-RNA: a web resource for eukaryotic RNA-binding proteins and their motifs. Nucleic Acids Res. 2025;gkaf1081. 10.1093/nar/gkaf1081. [DOI] [Google Scholar]
- 15. The RNAcentral Consortium . RNAcentral in 2026: genes and literature integration. Nucleic Acids Res. 2025;gkaf1329. 10.1093/nar/gkaf1329. [DOI] [Google Scholar]
- 16. Liu H, Yang Y, Le X et al. NONCODE v7.0: updated lncRNA resource integrating scRNA-seq data encompassing immune baseline, development, and disease. Nucleic Acids Res. 2025;gkaf1132. 10.1093/nar/gkaf1132. [DOI] [Google Scholar]
- 17. Sordyl D, Boileau E, Bernat A et al. MODOMICS: a database of RNA modifications and related information. 2025 update and 20th anniversary. Nucleic Acids Res. 2025;gkaf1284. 10.1093/nar/gkaf1284. [DOI] [Google Scholar]
- 18. Boileau E, Wilhelmi H, Busch A et al. Sci-ModoM: a quantitative database of transcriptome-wide high-throughput RNA modification sites. Nucleic Acids Res. 2025;53:D310–7. 10.1093/nar/gkae972. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19. Chuvochina M, Gerken J, Frentrup M et al. SILVA in 2026: a global core biodata resource for rRNA within the DSMZ digital diversity. Nucleic Acids Res. 2025;gkaf1247. 10.1093/nar/gkaf1247. [DOI] [Google Scholar]
- 20. Freese HM, Meier-Kolthoff JP, Sardà Carbasse J et al. TYGS and LPSN in 2025: a global core biodata resource for genome-based classification and nomenclature of prokaryotes within DSMZ digital diversity. Nucleic Acids Res. 2025;gkaf1110. 10.1093/nar/gkaf1110. [DOI] [Google Scholar]
- 21. Schober I, Koblitz J, Sardà Carbasse J et al. Bac Dive in 2025: the core database for prokaryotic strain data. Nucleic Acids Res. 2025;53:D748–56. 10.1093/nar/gkae959. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22. Berman H, Henrick K, Nakamura H et al. The worldwide protein data bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acids Res. 2007;35:D301–3. 10.1093/nar/gkl971. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23. Vallat B, Rose Y, Piehl DW et al. RCSB protein data bank: delivering integrative structures alongside experimental structures and computed structure models. Nucleic Acids Res. 2025;gkaf1187. 10.1093/nar/gkaf1187. [DOI] [Google Scholar]
- 24. Querino Lima Afonso M, Pidruchna I, Nair S et al. PDBe: enhanced structural data exploration to facilitate discovery. Nucleic Acids Res. 2025;gkaf1120. 10.1093/nar/gkaf1120. [DOI] [Google Scholar]
- 25. Bertoni D, Tsenkov M, Magana P et al. AlphaFold protein structure database 2025: a redesigned interface and updated structural coverage. Nucleic Acids Res. 2025;gkaf1226. 10.1093/nar/gkaf1226. [DOI] [Google Scholar]
- 26. UniProt Consortium . UniProt: the Universal Protein Knowledgebase in 2025. Nucleic Acids Res. 2025;53:D609–17. 10.1093/nar/gkae1010. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27. Lau AM, Bordin N, Kandathil SM et al. Exploring structural diversity across the protein universe with the encyclopedia of domains. Science. 2024;386:eadq4946. 10.1126/science.adq4946. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28. Mokhtari O, Bignon E, Khakzad H et al. DynaRepo: the repository of macromolecular conformational dynamics. Nucleic Acids Res. 2025;gkaf1130. 10.1093/nar/gkaf1130. [DOI] [Google Scholar]
- 29. Nugnes MV, Bouhraoua KEA, Zoubiri M et al. DisProt in 2026: enhancing intrinsically disordered proteins accessibility, deposition, and annotation. Nucleic Acids Res. 2025;gkaf1175. 10.1093/nar/gkaf1175. [DOI] [Google Scholar]
- 30. You K, Li R, Lian R et al. PhaSepDB 3.0: a comprehensive knowledgebase of phase separation-related proteins from AI-assisted curation. Nucleic Acids Res. 2025;gkaf973. 10.1093/nar/gkaf973. [DOI] [Google Scholar]
- 31. Kuznetsova K, Scheremetjew M, Yin J et al. CD-CODE 2.0: an enhanced condensate knowledgebase integrating pathobiology, condensate modulating drugs, and host-pathogen interactions. Nucleic Acids Res. 2025;gkaf1104. 10.1093/nar/gkaf1104. [DOI] [Google Scholar]
- 32. Sigrist CJA, Cuche BA, de Castro E et al. The PROSITE database for protein families, domains, and sites. Nucleic Acids Res. 2025;gkaf1188. 10.1093/nar/gkaf1188. [DOI] [Google Scholar]
- 33. Letunic I, Bork P. SMART v10: three decades of the protein domain annotation resource. Nucleic Acids Res. 2025;gkaf1023. 10.1093/nar/gkaf1023. [DOI] [Google Scholar]
- 34. Szklarczyk D, Nastou K, Koutrouli M et al. The STRING database in 2025: protein networks with directionality of regulation. Nucleic Acids Res. 2025;53:D730–7. 10.1093/nar/gkae1113. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35. Kanehisa M, Furumichi M, Sato Y et al. KEGG: biological systems database as a model of the real world. Nucleic Acids Res. 2025;53:D672–7. 10.1093/nar/gkae909. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36. The Gene Ontology Consortium . The Gene Ontology Knowledgebase in 2026. Nucleic Acids Res. 2025;gkaf1292. 10.1093/nar/gkaf1292. [DOI] [Google Scholar]
- 37. Hernández-Plaza A, Deng Z, Robledo-Yagüe F et al. eggNOG v7: phylogeny-based orthology predictions and functional annotations. Nucleic Acids Res. 2025;gkaf1249. 10.1093/nar/gkaf1249. [DOI] [Google Scholar]
- 38. Wang Y, Zhang Y, Wang X et al. GeneFamily: a comprehensive mammalian gene family database with extensive annotation and interactive visualization. Nucleic Acids Res. 2025;gkaf1195. 10.1093/nar/gkaf1195. [DOI] [Google Scholar]
- 39. Hauenstein J, Jeske L, Jäde A et al. BRENDA in 2026: a global core biodata resource for functional enzyme and metabolic data within the DSMZ digital diversity. Nucleic Acids Res. 2025;gkaf1113. 10.1093/nar/gkaf1113. [DOI] [Google Scholar]
- 40. Yuan L, Bianchi DM, Arneson K et al. Open enzyme database: a community-wide repository for sharing enzyme data. Nucleic Acids Res. 2025;gkaf1082. 10.1093/nar/gkaf1082. [DOI] [Google Scholar]
- 41. Lyu B, Wu K, Huang Y et al. GotEnzymes2: expanding coverage of enzyme kinetics and thermal properties. Nucleic Acids Res. 2025;gkaf1053. 10.1093/nar/gkaf1053. [DOI] [Google Scholar]
- 42. Rutz A, Probst D, Aguilar C et al. MITE: the minimum information about a tailoring enzyme database for capturing specialized metabolite biosynthesis. Nucleic Acids Res. 2025;gkaf969. 10.1093/nar/gkaf969. [DOI] [Google Scholar]
- 43. Long Y, Abbasinejad F, Li F-Z et al. Enzyme engineering database (EnzEngDB): a platform for sharing and interpreting sequence–function relationships across protein engineering campaigns. Nucleic Acids Res. 2025;gkaf1142. 10.1093/nar/gkaf1142. [DOI] [Google Scholar]
- 44. Ragueneau E, Gong C, Sinquin P et al. The reactome knowledgebase 2026. Nucleic Acids Res. 2025;gkaf1223. 10.1093/nar/gkaf1223. [DOI] [Google Scholar]
- 45. Lo Surdo P, Iannuccelli M, Karis K et al. SIGNOR 4.0: the 2025 update with focus on phosphorylation data. Nucleic Acids Res. 2025;1237. 10.1093/nar/gkaf1237. [DOI] [Google Scholar]
- 46. Türei D, Schaul J, Palacio-Escat N et al. OmniPath: integrated knowledgebase for multi-omics analysis. Nucleic Acids Res. 2025;gkaf1126. 10.1093/nar/gkaf1126. [DOI] [Google Scholar]
- 47. Neumann S, Meier R, Wenk M et al. MassBank: an open and FAIR mass spectral data resource. Nucleic Acids Res. 2025;gkaf1193. 10.1093/nar/gkaf1193. [DOI] [Google Scholar]
- 48. Catoiu EA, Kambo D, Rodriguez B et al. QSProteome: a community-driven interactive platform for large-scale exploration and evaluation of predicted protein complex structures. Nucleic Acids Res. 2025;gkaf1099. 10.1093/nar/gkaf1099. [DOI] [Google Scholar]
- 49. Zhou N, Peng L, Luo Q et al. FerrDb V3: expanding the manually curated resource for regulators and disease associations from ferroptosis to regulated cell death. Nucleic Acids Res. 2025;gkaf1119. 10.1093/nar/gkaf1119. [DOI] [Google Scholar]
- 50. Parks DH, Chaumeil PA, Mussig AJ et al. GTDB release 10: a complete and systematic taxonomy for 715 230 bacterial and 17 245 archaeal genomes. Nucleic Acids Res. 2025;gkaf1040. 10.1093/nar/gkaf1040. [DOI] [Google Scholar]
- 51. Black EJ, Powell CS, Dempsey DM et al. Virus taxonomy: the database of the international committee on taxonomy of viruses. Nucleic Acids Res. 2025;gkaf1159. 10.1093/nar/gkaf1159. [DOI] [Google Scholar]
- 52. Huang C, Huang H, Ding M et al. ViMIC 2.0: an updated database of human disease-related viral mutations, integration sites, and multi-omics data. Nucleic Acids Res. 2025;gkaf1106. 10.1093/nar/gkaf1106. [DOI] [Google Scholar]
- 53. Zhang X, Yang S, Xu X et al. scMOVIR: a single-cell multi-omics database for human viral infections and immune responses. Nucleic Acids Res. 2025;gkaf1153. 10.1093/nar/gkaf1153. [DOI] [Google Scholar]
- 54. Nishijima S, Fullam A, Schmidt TSB et al. VIRE: a metagenome-derived, planetary-scale virome resource with environmental context. Nucleic Acids Res. 2025;gkaf1225. 10.1093/nar/gkaf1225. [DOI] [Google Scholar]
- 55. Schmidt TS, Fullam A, Ferretti P et al. SPIRE: a searchable, planetary-scale mIcrobiome REsource. Nucleic Acids Res. 2024;52:D777–83. 10.1093/nar/gkad943. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 56. Kuhn M, Schmidt TSB, Ferretti P et al. Metalog: curated and harmonised contextual data for global metagenomics samples. Nucleic Acids Res. 2025;gkaf1118. 10.1093/nar/gkaf1118. [DOI] [Google Scholar]
- 57. Fiamenghi MB, Camargo AP, Chasapi IN et al. Meta-virus resource (MetaVR): expanding the frontiers of viral diversity with 24 million uncultivated virus genomes. Nucleic Acids Res. 2025;gkaf1283. 10.1093/nar/gkaf1283. [DOI] [Google Scholar]
- 58. Camargo AP, Nayfach S, Chen IM et al. IMG/VR v4: an expanded database of uncultivated virus genomes within a framework of extensive functional, taxonomic, and ecological metadata. Nucleic Acids Res. 2023;51:D733–43. 10.1093/nar/gkac1037. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 59. Gambhir S, Pandey S, Bajetha H et al. ARKbase: antimicrobial resistance knowledgebase1.0. Nucleic Acids Res. 2025;gkaf1307. 10.1093/nar/gkaf1307. [DOI] [Google Scholar]
- 60. Cerdeira LT, Dyson ZA, Sharma V et al. AMRnet: a data visualization platform to interactively explore pathogen variants and antimicrobial resistance. Nucleic Acids Res. 2025;gkaf1101. 10.1093/nar/gkaf1101. [DOI] [Google Scholar]
- 61. Liu C, Wang X, Zhang Z et al. GMrepo v3: a curated human gut microbiome database with expanded disease coverage and enhanced cross-dataset biomarker analysis. Nucleic Acids Res. 2025;gkaf1190. 10.1093/nar/gkaf1190. [DOI] [Google Scholar]
- 62. Qian K, Du M, Tan S et al. gutMSNP: a comprehensive database for human gut microbial single-nucleotide polymorphisms. Nucleic Acids Res. 2025;gkaf1205. 10.1093/nar/gkaf1205. [DOI] [Google Scholar]
- 63. Ji X, Qian Q, Zhang H et al. ResMicroDb: a comprehensive database and analysis platform for the human respiratory microbiome. Nucleic Acids Res. 2025;gkaf1194. 10.1093/nar/gkaf1194. [DOI] [Google Scholar]
- 64. Nagasaki M, Katayama T, Moriya Y et al. JoGo 1.0: the ACTG hierarchical nomenclature and database covering 4.7 million haplotypes across 19,194 human genes. Nucleic Acids Res. 2025;gkaf1232. 10.1093/nar/gkaf1232. [DOI] [Google Scholar]
- 65. Morales J, Pujar S, Loveland JE et al. A joint NCBI and EMBL-EBI transcript set for clinical genomics and research. Nature. 2022;604:310–5. 10.1038/s41586-022-04558-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 66. Landrum MJ, Chitipiralla S, Kaur K et al. ClinVar: updates to support classifications of both germline and somatic variants. Nucleic Acids Res. 2025;53:D1313–21. 10.1093/nar/gkae1090. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 67. Cerezo M, Sollis E, Ji Y et al. The NHGRI-EBI GWAS catalog: standards for reusability, sustainability and diversity. Nucleic Acids Res. 2025;53:D998–1005. 10.1093/nar/gkae1070. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 68. Lonsdale J, Thomas J, Salvatore M et al. The genotype-tissue expression (GTEx) project. Nat Genet. 2013;45:580–5. 10.1038/ng.2653. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 69. Zhao H, Yin X, Wang S et al. So3D: a comprehensive three-dimensional spatial omics resource for decoding tissue architecture in physiology and disease. Nucleic Acids Res. 2025;gkaf998. 10.1093/nar/gkaf998. [DOI] [Google Scholar]
- 70. Kang H, Jing X, Lin J et al. Spatial GWAS Atlas: a knowledgebase for decoding the genetic architecture of complex traits in spatial resolution. Nucleic Acids Res. 2025;gkaf1103. 10.1093/nar/gkaf1103. [DOI] [Google Scholar]
- 71. Hu X, Wang A, Yu H et al. Spatial2GWAS: a database for linking spatial transcriptomic regions with GWAS traits. Nucleic Acids Res. 2025;gkaf1047. 10.1093/nar/gkaf1047. [DOI] [Google Scholar]
- 72. Wlasnowolski M, Kozlov N, Wojcik M et al. enhancer3D: 3D chromatin structures and enhancer-promoter distance profiles for archaic and modern human genomes. Nucleic Acids Res. 2025;gkaf1256. 10.1093/nar/gkaf1256. [DOI] [Google Scholar]
- 73. Chen M, Du L, Zhao S et al. ChromPolymerDB: a high-resolution database of single-cell 3D chromatin structures for functional genomics. Nucleic Acids Res. 2025;gkaf1233. 10.1093/nar/gkaf1233. [DOI] [Google Scholar]
- 74. Yates AD, Austine-Orimoloye O, Azov AG et al. Ensembl 2026. Nucleic Acids Res. 2025;gkaf1239. 10.1093/nar/gkaf1239. [DOI] [Google Scholar]
- 75. Casper J, Speir ML, Raney BJ et al. The UCSC genome browser database: 2026 update. Nucleic Acids Res. 2025;gkaf1250. 10.1093/nar/gkaf1250. [DOI] [Google Scholar]
- 76. Rubin AF, Stone J, Bianchi AH et al. MaveDB 2024: a curated community database with over seven million variant effects from multiplexed functional assays. Genome Biol. 2025;26:13. 10.1186/s13059-025-03476-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 77. Barker DJ, Natarajan RHL, Cooper MA et al. The IPD-IMGT/HLA database: recent developments in sequence submission. Nucleic Acids Res. 2025;gkaf1218. 10.1093/nar/gkaf1218. [DOI] [Google Scholar]
- 78. Sanou G, Zeitoun G, Manso T et al. IMGT® at scale: FAIR, dynamic, and automated tools for immune locus analysis. Nucleic Acids Res. 2025;gkaf1024. 10.1093/nar/gkaf1024. [DOI] [Google Scholar]
- 79. Liu R, Tang Q, Sun P et al. iFish: a comprehensive multi-omics database for fish genetics, transcriptional regulation, and epigenetic research. Nucleic Acids Res. 2025;gkaf1026. 10.1093/nar/gkaf1026. [DOI] [Google Scholar]
- 80. She J, Qian PY, Wu L. DOO: integrated multi-omics resources for deep ocean organisms. Nucleic Acids Res. 2025;gkaf1096. 10.1093/nar/gkaf1096. [DOI] [Google Scholar]
- 81. Seal RL, Braschi B, Gray K et al. Genenames.org: the HGNC and PGNC resources in 2026. Nucleic Acids Res. 2025;gkaf1229. 10.1093/nar/gkaf1229. [DOI] [Google Scholar]
- 82. Feng X, Zheng J, Peng S et al. CNAScope: pan-cancer copy number aberration database with functional annotation and interactive visualization. Nucleic Acids Res. 2025;gkaf1242. 10.1093/nar/gkaf1242. [DOI] [Google Scholar]
- 83. Huang R, Li J, Cao Q et al. PCsRNAdb: a comprehensive resource of small noncoding RNAs across cancers. Nucleic Acids Res. 2025;gkaf992. 10.1093/nar/gkaf992. [DOI] [Google Scholar]
- 84. Chen Y, Zhang L, Zhong C et al. Rare Cancer Explorer 1.0 (RaCE 1.0): a dedicated database and analytical platform focused on rare cancers. Nucleic Acids Res. 2025;gkaf911. 10.1093/nar/gkaf911. [DOI] [Google Scholar]
- 85. Ma S, Jiang J, Zhang R et al. scCT-DB, an omnibus for cancer patient-derived paired pre- and post-treatment single-cell transcriptomes to reveal drug perturbation and drug resistance mechanisms. Nucleic Acids Res. 2025;gkaf1065. 10.1093/nar/gkaf1065. [DOI] [Google Scholar]
- 86. Meng X, Nie Z, Wang Q et al. TE-SCALE: a comprehensive database for exploring transposable element expression across human cancers at single-cell resolution. Nucleic Acids Res. 2025;gkaf1235. 10.1093/nar/gkaf1235. [DOI] [Google Scholar]
- 87. Cho M, Tang G, Rogers CS et al. OncoDB 2.0: a comprehensive platform for integrated pan-cancer omics analysis. Nucleic Acids Res. 2025;gkaf952. 10.1093/nar/gkaf952. [DOI] [Google Scholar]
- 88. Benard BA, Lalgudi CK, Ilerten I et al. PRECOG update: an augmented resource of clinical outcome associations with gene expression for adult, pediatric, and immunotherapy cohorts. Nucleic Acids Res. 2025;gkaf1215. 10.1093/nar/gkaf1215. [DOI] [Google Scholar]
- 89. Zhou H, Verma V, Li Z et al. FAVOR 2.0: a reengineered functional annotation of variants online resource for interpreting genomic variation. Nucleic Acids Res. 2025;gkaf1217. 10.1093/nar/gkaf1217. [DOI] [Google Scholar]
- 90. Li D, Liu S, Assis PR et al. The IGVF catalog—from genetic variation to function. Nucleic Acids Res. 2025;gkaf1341. 10.1093/nar/gkaf1341. [DOI] [Google Scholar]
- 91. Jiang T, Shao M, Wang J et al. GENEasso: a curated resource of credible disease-gene associations across complex diseases from GWAS summary statistics. Nucleic Acids Res. 2025;gkaf1097. 10.1093/nar/gkaf1097. [DOI] [Google Scholar]
- 92. Zhang Y, Zhou Y, Xu H et al. Therapeutic target database 2026: facilitating targeted therapies and precision medicine. Nucleic Acids Res. 2025;gkaf1154. 10.1093/nar/gkaf1154. [DOI] [Google Scholar]
- 93. Zheng J, Chen S, Zhang Y et al. PMADS: an integrated database of curated and proteomics-inferred associations between protein post-translational modifications and drug sensitivity. Nucleic Acids Res. 2025;gkaf1033. 10.1093/nar/gkaf1033. [DOI] [Google Scholar]
- 94. Li Y, Yang F, Pan Z et al. VARIDT 4.0: distribution variability of drug transporters. Nucleic Acids Res. 2025;gkaf981. 10.1093/nar/gkaf981. [DOI] [Google Scholar]
- 95. Sun X, Wei Z, Yu X et al. DRESIS 2.0: the comprehensive landscape of drug resistance information. Nucleic Acids Res. 2025;gkaf1219. 10.1093/nar/gkaf1219. [DOI] [Google Scholar]
- 96. Harding SD, Armstrong JF, Faccenda E et al. The IUPHAR/BPS guide to PHARMACOLOGY in 2026. Nucleic Acids Res. 2025;gkaf1067. 10.1093/nar/gkaf1067. [DOI] [Google Scholar]
- 97. Zhou Y, Hu Y, Zhang L et al. theRNA: a curated knowledgebase of functional RNA therapeutics spanning diverse modalities and disease applications. Nucleic Acids Res. 2025;gkaf1064. 10.1093/nar/gkaf1064. [DOI] [Google Scholar]
- 98. Liu J, Liu X, Zhang Y et al. RadioPharm: the database of radiopharmaceuticals. Nucleic Acids Res. 2025;gkaf1021. 10.1093/nar/gkaf1021. [DOI] [Google Scholar]
- 99. Jiang M, Liu T, Hussain M et al. Macrocycle-DB: a comprehensive database for macrocycle-based drug discovery. Nucleic Acids Res. 2025;gkaf1107. 10.1093/nar/gkaf1107. [DOI] [Google Scholar]
- 100. Qin X, Zhang Y, Wang Y et al. TPDdb: the comprehensive database of targeted protein degrader. Nucleic Acids Res. 2025;gkaf996. 10.1093/nar/gkaf996. [DOI] [Google Scholar]
- 101. Li C, Luo H, Pang Y et al. MGDB: a curated database for molecular glues. Nucleic Acids Res. 2025;gkaf1131. 10.1093/nar/gkaf1131. [DOI] [Google Scholar]
- 102. Zhu J, Liao Y, Lin H et al. MGTbind: a comprehensive database of molecular glue ternary interactome. Nucleic Acids Res. 2025;gkaf1075. 10.1093/nar/gkaf1075. [DOI] [Google Scholar]
- 103. Wang X, Zhuang Z, Zhang C et al. MolGlueDB: an online database of molecular glues. Nucleic Acids Res. 2025;gkaf811. 10.1093/nar/gkaf811. [DOI] [Google Scholar]
- 104. Olson A, Kumari S, Wei X et al. Gramene 2025: expanded comparative genomics and pathway resources, integrated search, and pan-genome portals for crop research. Nucleic Acids Res. 2025;gkaf1260. 10.1093/nar/gkaf1260. [DOI] [Google Scholar]
- 105. Sharma A, Bowers JE, Lee TH et al. PGDD 2.0: plant Genome Duplication Database with updated content and tools. Nucleic Acids Res. 2025;gkaf1287. 10.1093/nar/gkaf1287. [DOI] [Google Scholar]
- 106. Endo M, Ito M, Kubota A et al. GEAR: an integrated atlas of gene expression dynamics in Arabidopsis thaliana. Nucleic Acids Res. 2025;gkaf1056. 10.1093/nar/gkaf1056. [DOI] [Google Scholar]
- 107. Chasapi MN, Chasapi IN, Aplakidou E et al. metagRoot: a comprehensive database of protein families associated with plant root microbiomes. Nucleic Acids Res. 2025;gkaf862. 10.1093/nar/gkaf862. [DOI] [Google Scholar]
- 108. Aguilar C, Fontove-Herrera F, Pashkov A et al. MicroAgroBiome: a toolkit for exploring specialized metabolism and ecological interactions in rhizosphere microbiomes of cultivated crops. Nucleic Acids Res. 2025;gkaf1083. 10.1093/nar/gkaf1083. [DOI] [Google Scholar]
- 109. Malik A, Arsalan M, Moreno C et al. ChEBI: re-engineered for a sustainable future. Nucleic Acids Res. 2025;gkaf1271. 10.1093/nar/gkaf1271. [DOI] [Google Scholar]
- 110. Thakar K, Madhugiri I, Gadgil C et al. MediaAssist: database to support the design and optimization of cell culture medium. Nucleic Acids Res. 2025;gkaf982. 10.1093/nar/gkaf982. [DOI] [Google Scholar]
