An ontology for cell types

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“Gray's Anatomy”

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Creating the Gene Ontology Resource: Design and ImplementationPreprint

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MOLECULAR BIOLOGY OF THE CELL, 5TH EDITION

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Creating the gene ontology resource: design and implementation.

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Drosophila crinkled, Mutations of Which Disrupt Morphogenesis and Cause Lethality, Encodes Fly Myosin VIIA

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Phenotypic data in FlyBase

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Gene Ontology Consortium: going forward

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The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration

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The IUPHAR/BPS Guide to PHARMACOLOGY in 2018: updates and expansion to encompass the new guide to IMMUNOPHARMACOLOGY

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Relations in biomedical ontologies

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Uberon, an integrative multi-species anatomy ontology

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Expansion of the Human Phenotype Ontology (HPO) knowledge base and resources

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Supervised classification enables rapid annotation of cell atlases

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ArrayExpress update--from an archive of functional genomics experiments to the atlas of gene expression

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CZ CELLxGENE Discover: a single-cell data platform for scalable exploration, analysis and modeling of aggregated data

Program, C. C. S., Abdulla, S., Aevermann, B., Assis, P., Badajoz, S., Bell, S. M., Bezzi, E., Cakir, B., Chaffer, J., Chambers, S., et al. (2025) · Nucleic Acids Research · doi:10.1093/nar/gkae1142 · Cited by 399

Bio-ontologies: current trends and future directions

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The Human Phenotype Ontology

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The mammalian phenotype ontology: enabling robust annotation and comparative analysis

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The Cell Ontology 2016: enhanced content, modularization, and ontology interoperability

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Developmental Fate and Cellular Maturity Encoded in Human Regulatory DNA Landscapes

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Integrating phenotype ontologies across multiple species

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Linking Human Diseases to Animal Models Using Ontology-Based Phenotype Annotation

Washington, N. L., Haendel, M. A., Mungall, C., Ashburner, M., Westerfield, M., & Lewis, S. (2009) · PLoS Biology · doi:10.1371/journal.pbio.1000247 · Cited by 277

OBO-Edit—an ontology editor for biologists

Day-Richter, J., Harris, M. A., Haendel, M. A., The Gene Ontology OBO-Edit Working Group, & Lewis, S. (2007) · Bioinformatics · doi:10.1093/bioinformatics/btm112 · Cited by 277

Concept annotation in the CRAFT corpus

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A Chado case study: an ontology-based modular schema for representing genome-associated biological information

Mungall, C., & Emmert, D. B. (2007) · Bioinformatics · doi:10.1093/bioinformatics/btm189 · Cited by 250

Unsupervised biomedical named entity recognition: Experiments with clinical and biological texts

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A Review of Single-Cell RNA-Seq Annotation, Integration, and Cell–Cell Communication

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The Foundational Model of Anatomy Ontology

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ZFIN: enhancements and updates to the zebrafish model organism database

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Protein Family Expansions and Biological Complexity

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PhenomeNET: a whole-phenome approach to disease gene discovery

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Universal cell embedding provides a foundation model for cell biology

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FlyBase: anatomical data, images and queries

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Automated Acquisition of Disease-Drug Knowledge from Biomedical and Clinical Documents: An Initial Study

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General Formal Ontology (GFO): A Foundational Ontology for Conceptual Modelling

Heinrich Herre, B. (2010) · Springer eBooks · doi:10.1007/978-90-481-8847-5_14 · Cited by 204

Elucidation of seventeen human peripheral blood B‐cell subsets and quantification of the tetanus response using a density‐based method for the automated identification of cell populations in multidimensional flow cytometry data

Qian, Y., Wei, C., Lee, F. E.-H., Campbell, J. P., Halliley, J. L., Lee, J. A., Cai, J. X., Kong, Y. M., Sadat, E. L., Thomson, E., et al. (2010) · Cytometry Part B Clinical Cytometry · doi:10.1002/cyto.b.20554 · Cited by 196

The IUPHAR/BPS Guide to PHARMACOLOGY in 2020: extending immunopharmacology content and introducing the IUPHAR/MMV Guide to MALARIA PHARMACOLOGY

Armstrong, J. F., Faccenda, E., Harding, S. D., Pawson, A. J., Southan, C., Sharman, J. L., Campo, B., Cavanagh, D. R., Alexander, S. P. H., Davenport, A. P., et al. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz951 · Cited by 186

Gene Ontology annotations: what they mean and where they come from

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The Adult Mouse Anatomical Dictionary: a tool for annotating and integrating data

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MIREOT: The minimum information to reference an external ontology termPreprint

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The BRENDA Tissue Ontology (BTO): the first all-integrating ontology of all organisms for enzyme sources

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Identification of disease treatment mechanisms through the multiscale interactome

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Managing, Analysing, and Integrating Big Data in Medical Bioinformatics: Open Problems and Future Perspectives

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scClassify: sample size estimation and multiscale classification of cells using single and multiple reference

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A guide to best practices for Gene Ontology (GO) manual annotation

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Applications of single-cell and bulk RNA sequencing in onco-immunology

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The Plant Ontology Database: a community resource for plant structure and developmental stages controlled vocabulary and annotations

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The BLUEPRINT Data Analysis Portal

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The mouse Gene Expression Database (GXD): 2021 update

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CZ CELL×GENE Discover: A single-cell data platform for scalable exploration, analysis and modeling of aggregated data

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Standards for systems biology

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Logical Development of the Cell Ontology

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WebCSEA: web-based cell-type-specific enrichment analysis of genes

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Phenotype ontologies: the bridge between genomics and evolution

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PRIDE: new developments and new datasets

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Cross-Product Extensions of the Gene Ontology

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Infectious Disease Ontology

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Large-scale biomedical concept recognition: an evaluation of current automatic annotators and their parameters

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BIOINFORMATICS AND ITS APPLICATIONS IN PLANT BIOLOGY

Rhee, S. Y., Dickerson, J. A., & Xu, D. H. (2006) · Annual Review of Plant Biology · doi:10.1146/annurev.arplant.56.032604.144103 · Cited by 120

BioTop: An upper domain ontology for the life sciences

Beißwanger, E., Schulz, S., Stenzhorn, H., & Hahn, U. (2008) · Applied Ontology · doi:10.3233/ao-2008-0057 · Cited by 116

Minimum information specification for in situ hybridization and immunohistochemistry experiments (MISFISHIE)

Deutsch, E. W., Ball, C. A., Berman, J. J., Bova, G. S., Brāzma, A., Bumgarner, R. E., Campbell, D. S., Causton, H. C., Christiansen, J. H., Daian, F., et al. (2008) · Nature Biotechnology · doi:10.1038/nbt1391 · Cited by 116

Annotated genes and nonannotated genomes: cross‐species use of Gene Ontology in ecology and evolution research

Primmer, C. R., Papakostas, S., Leder, E. H., Davis, M. J., & Ragan, M. A. (2013) · Molecular Ecology · doi:10.1111/mec.12309 · Cited by 122

MOPED: Model Organism Protein Expression Database

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A reference cell tree will serve science better than a reference cell atlas

Domcke, S., & Shendure, J. (2023) · Cell · doi:10.1016/j.cell.2023.02.016 · Cited by 113

Obol: integrating language and meaning in bio‐ontologies

Mungall, C. (2004) · Comparative and Functional Genomics · doi:10.1002/cfg.435 · Cited by 110

The neuron classification problem

Bota, M., & Swanson, L. W. (2007) · Brain Research Reviews · doi:10.1016/j.brainresrev.2007.05.005 · Cited by 108

The Plant Structure Ontology, a Unified Vocabulary of Anatomy and Morphology of a Flowering Plant

Ilic, K., Kellogg, E. A., Jaiswal, P., Zapata, F., Stevens, P. F., Vincent, L., Avraham, S., Reiser, L., Pujar, A., Sachs, M. M., et al. (2006) · PLANT PHYSIOLOGY · doi:10.1104/pp.106.092825 · Cited by 107

A multilevel data integration resource for breast cancer study

Mosca, E., Alfieri, R. R., Merelli, I., Viti, F., Calabria, A., & Milanesi, L. (2010) · BMC Systems Biology · doi:10.1186/1752-0509-4-76 · Cited by 102

Combining rules and machine learning for extraction of temporal expressions and events from clinical narratives

Kovačević, A., Dehghan, A., Filannino, M., Keane, J. A., & Nenadić, G. (2013) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2013-001625 · Cited by 91

The Software Ontology (SWO): a resource for reproducibility in biomedical data analysis, curation and digital preservation

MALONE, J. M., Brown, A. J., Lister, A., Ison, J., Hull, D., Parkinson, H., & Stevens, R. (2014) · Journal of Biomedical Semantics · doi:10.1186/2041-1480-5-25 · Cited by 90

Overview of the Cancer Genetics and Pathway Curation tasks of BioNLP Shared Task 2013

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The Cell Centered Database project: An update on building community resources for managing and sharing 3D imaging data

Martone, M. E., Tran, J., Wong, W., Sargis, J., Fong, L., Larson, S., Lamont, S., Gupta, A., & Ellisman, M. H. (2007) · Journal of Structural Biology · doi:10.1016/j.jsb.2007.10.003 · Cited by 88

Functional clustering and lineage markers: Insights into cellular differentiation and gene function from large-scale microarray studies of purified primary cell populations

Hume, D. A., SUMMERS, K. M., Raza, S., Baillie, J. K., & Freeman, T. C. (2010) · Genomics · doi:10.1016/j.ygeno.2010.03.002 · Cited by 89

MetaSRA: normalized human sample-specific metadata for the Sequence Read Archive

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Phen2Gene: rapid phenotype-driven gene prioritization for rare diseases

Zhao, M., Havrilla, J. M., Li, F., Chen, Y., Peng, J. J., Liu, C., Wu, C., Sarmady, M., Botas, P., Isla, J., et al. (2020) · NAR Genomics and Bioinformatics · doi:10.1093/nargab/lqaa032 · Cited by 91

Entity/quality-based logical definitions for the human skeletal phenome using PATO

Gkoutos, G. V., Mungall, C., Doelken, S. C., Ashburner, M., Lewis, S., Hancock, J. M., Schofield, P. N., Köhler, S., & Robinson, P. N. (2009) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/iembs.2009.5333362 · Cited by 87

Construction and accessibility of a cross-species phenotype ontology along with gene annotations for biomedical research

Köhler, S., Doelken, S. C., Ruef, B. J., Bauer, S., Washington, N. L., Westerfield, M., Gkoutos, G. V., Schofield, P. N., Smedley, D. P., Lewis, S., et al. (2013) · F1000Research · doi:10.12688/f1000research.2-30.v2 · Cited by 85

MirZ: an integrated microRNA expression atlas and target prediction resource

Hausser, J., Berninger, P., Rodak, C., Jantscher, Y., Wirth, S., & Zavolan, M. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkp412 · Cited by 83

Tempora: Cell trajectory inference using time-series single-cell RNA sequencing data

Tran, T. N., & Bader, G. D. (2020) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1008205 · Cited by 82

A review on knowledge graphs for healthcare: Resources, applications, and promises

Cui, H., Lu, J., Xu, R., Wang, S.-Y., Ma, W., Yu, Y., Yu, S., Kan, X., Ling, C., Zhao, L., et al. (2025) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2025.104861 · Cited by 102

Leveraging the Cell Ontology to classify unseen cell types

Wang, S., Pisco, A. O., McGeever, A., Brbić, M., Žitnik, M., Darmanis, S., Leskovec, J., Karkanias, J., & Altman, R. B. (2021) · Nature Communications · doi:10.1038/s41467-021-25725-x · Cited by 84

A machine learning method for the discovery of minimum marker gene combinations for cell type identification from single-cell RNA sequencingPreprint

Aevermann, B. D., Zhang, Y., Novotny, M. A., Keshk, M., Bakken, T. E., Miller, J. A., Hodge, R. D., Lelieveldt, B. P. F., Lein, E. S., & Scheuermann, R. H. (2021) · Genome Research · doi:10.1101/gr.275569.121 · Cited by 77

Vision, challenges and opportunities for a Plant Cell Atlas

Ahmed, J., Alaba, O., Ameen, G., Arora, V., Arteaga-Vazquez, M. A., Arun, A., Bailey-Serres, J. N., Bartley, L., Bassel, G. W., Bergmann, D. C., et al. (2021) · eLife · doi:10.7554/elife.66877 · Cited by 80

Mapping the multiscale structure of biological systems

Schaffer, L. V., & Ideker, T. (2021) · Cell Systems · doi:10.1016/j.cels.2021.05.012 · Cited by 75

Immune-centric network of cytokines and cells in disease context identified by computational mining of PubMed

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PHENOGO: ASSIGNING PHENOTYPIC CONTEXT TO GENE ONTOLOGY ANNOTATIONS WITH NATURAL LANGUAGE PROCESSING

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A versatile platform for comprehensive chip‐based explorative cytometry

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NeuroMorpho.Org Implementation of Digital Neuroscience: Dense Coverage and Integration with the NIF

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Immunology Driven by Large-Scale Single-Cell Sequencing

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Cistrome Data Browser: integrated search, analysis and visualization of chromatin data

Taing, L., Dandawate, A., L’Yi, S., Gehlenborg, N., Brown, M. A., & Meyer, C. A. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad1069 · Cited by 71

DeepBlue epigenomic data server: programmatic data retrieval and analysis of epigenome region sets

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Early immunologic correlates of HIV protection can be identified from computational analysis of complex multivariate T-cell flow cytometry assays

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A Tutorial on Hierarchical Classification with Applications in Bioinformatics

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