Impact of the Human Cell Atlas on medicine

Spatial reconstruction of single-cell gene expression data

Satija, R., Farrell, J. A., Gennert, D., Schier, A. F., & Regev, A. (2015) · Nature Biotechnology · doi:10.1038/nbt.3192 · Cited by 7,055

Oncology meets immunology: the cancer-immunity cycle.

Chen, D. S., & Mellman, I. (2013) · Immunity · doi:10.1016/j.immuni.2013.07.012 · Cited by 6,929

A Unique Microglia Type Associated with Restricting Development of Alzheimer’s Disease

Keren-Shaul, H., Spinrad, A., Weiner, A., Matcovitch-Natan, O., Dvir-Szternfeld, R., Ulland, T. K., David, E., Baruch, K., Lara-Astaiso, D., Toth, B., et al. (2017) · Cell · doi:10.1016/j.cell.2017.05.018 · Cited by 5,493

SARS-CoV-2 entry factors are highly expressed in nasal epithelial cells together with innate immune genes

HCA Lung Biological Network, Sungnak, W., Huang, N., Bécavin, C., Berg, M., Queen, R., Litvinukova, M., Talavera-López, C., Maatz, H., Reichart, D., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-0868-6 · Cited by 2,501

Single-cell RNA-seq data analysis on the receptor ACE2 expression reveals the potential risk of different human organs vulnerable to 2019-nCoV infection

Zou, X., Chen, K., Zou, J., Han, P., Hao, J., & Han, Z. (2020) · Frontiers of Medicine · doi:10.1007/s11684-020-0754-0 · Cited by 2,287

SARS-CoV-2 Receptor ACE2 Is an Interferon-Stimulated Gene in Human Airway Epithelial Cells and Is Detected in Specific Cell Subsets across Tissues

Ziegler, C. G. K., Allon, S. J., Nyquist, S. K., Mbano, I. M., Miao, V. N., Tzouanas, C. N., Cao, Y., Yousif, A. S., Bals, J., Hauser, B. M., et al. (2020) · Cell · doi:10.1016/j.cell.2020.04.035 · Cited by 2,284

The human cell atlas

Regev, A., Teichmann, S. A., Lander, E. S., Amit, I., Benoist, C., Birney, E., Bodenmiller, B., Campbell, P., Carninci, P., Clatworthy, M., et al. (2017) · eLife · doi:10.7554/elife.27041 · Cited by 2,232

Complex cell-state changes revealed by single cell RNA sequencing of 76,149 microglia throughout the mouse lifespan and in the injured brain

Hammond, T. R., Dufort, C., Dissing-Olesen, L., Giera, S., Young, A., Wysoker, A., Walker, A. J., Segel, M., Nemesh, J., Saunders, A., et al. (2018) · doi:10.1101/406140 · Cited by 2,225

Defining T Cell States Associated with Response to Checkpoint Immunotherapy in Melanoma

Sade-Feldman, M., Yizhak, K., Bjorgaard, S. L., Ray, J. P., de Boer, C. G., Jenkins, R. W., Lieb, D. J., Chen, J. H., Frederick, D. T., Barzily-Rokni, M., et al. (2018) · Cell · doi:10.1016/j.cell.2018.10.038 · Cited by 2,053

Perturb-Seq: Dissecting Molecular Circuits with Scalable Single-Cell RNA Profiling of Pooled Genetic Screens

Dixit, A., Parnas, O., Li, B., Chen, J., Fulco, C. P., Jerby-Arnon, L., Marjanovic, N. D., Dionne, D., Burks, T., Raychowdhury, R., et al. (2016) · Cell · doi:10.1016/j.cell.2016.11.038 · Cited by 1,863

An atlas of cell-type-specific interactome networks across 44 human tumor types

Li, Z., Liu, G., Yang, X., Shu, M., Jin, W., Tong, Y., Liu, X., Wang, Y., Yuan, J., & Yang, Y. (2024) · Genome Medicine · doi:10.1186/s13073-024-01303-w · Cited by 10

Integrating bulk, single-cell, and spatial transcriptomics to identify and functionally validate novel targets to enhance immunotherapy in NSCLC

Cao, K., Wei, S., Ma, T., Yang, X., Wang, Y., He, X., Lu, M., Bai, Y., Qi, C., Zhang, L., et al. (2025) · npj Precision Oncology · doi:10.1038/s41698-025-00893-x · Cited by 10

Multistep genomics on single cells and live cultures in subnanoliter capsules

Mazelis, I., Sun, H., Kulkarni, A., Torre, T. L., & Klein, A. M. (2025) · Science · doi:10.1126/science.ady7209 · Cited by 13

Toward a new nosology of neurodegenerative diseases

Menéndez‐González, M. (2023) · Alzheimer s & Dementia · doi:10.1002/alz.13041 · Cited by 12

Decoding Human Biology and Disease Using Single-Cell Omics Technologies

Shi, Q., Chen, X., & Zhang, Z. (2023) · Genomics Proteomics & Bioinformatics · doi:10.1016/j.gpb.2023.06.003 · Cited by 11

The Hong Kong genome project: building genome sequencing capacity and capability for advancing genomic science in Hong Kong

Chu, A. T.-W., Tong, A. H. Y., Tse, D. M.-S., Lo, C. W. S., Lau, C. C. F., Li, C. Y. F., Tai, N. S. Y., Wong, L. W., Choy, G., Tse, B. Y. Y., et al. (2023) · Journal of Translational Genetics and Genomics · doi:10.20517/jtgg.2023.22 · Cited by 9

Systems analysis of human innate immunity in COVID-19

Müller, S. M., & Schultze, J. L. (2023) · Seminars in Immunology · doi:10.1016/j.smim.2023.101778 · Cited by 9

Understanding the key challenges in tuberculosis drug discovery: what does the future hold?

Zein-Eddine, R., Ramuz, M., Refrégier, G., Lutzeyer, J. F., Aleksandrov, A. V., & Myllykallio, H. (2025) · Expert Opinion on Drug Discovery · doi:10.1080/17460441.2025.2531229 · Cited by 9

Reusability report: Exploring the transferability of self-supervised learning models from single-cell to spatial transcriptomics

Han, C., Lin, S., Wang, Z., Cui, Y., Zou, Q., & Yuan, Z. (2025) · Nature Machine Intelligence · doi:10.1038/s42256-025-01097-5 · Cited by 8

Learning multi-cellular representations of single-cell transcriptomics data enables characterization of patient-level disease states

Liu, T., Brouwer, E. D., Verma, A., Missarova, A., Kuo, T. C.-Y., Diamant, N., Wang, H., Hao, M., Biancalani, T., Bravo, H. C., et al. (2026) · Cell Systems · doi:10.1016/j.cels.2026.101570 · Cited by 9

Initial Phase of Anthracycline Cardiotoxicity Involves Cardiac Fibroblasts Activation and Metabolic Switch

Telesca, M., Donniacuo, M., Bellocchio, G., Riemma, M. A., Mele, E., Dell’Aversana, C., Sgueglia, G., Cianflone, E., Cappetta, D., Torella, D., et al. (2023) · Cancers · doi:10.3390/cancers16010053 · Cited by 8

Multi-Objective Genetic Algorithm for Cluster Analysis of Single-Cell Transcriptomes

Zhao, K., Grayson, J. M., & Khuri, N. (2023) · Journal of Personalized Medicine · doi:10.3390/jpm13020183 · Cited by 9

hadge: a comprehensive pipeline for donor deconvolution in single-cell studies

Curion, F., Wu, X., Heumos, L., André, M. M. G., Halle, L., Ozols, M., Grant‐Peters, M., Rich‐Griffin, C., Yeung, H., Dendrou, C. A., et al. (2024) · Genome biology · doi:10.1186/s13059-024-03249-z · Cited by 10

IOBR2: Multidimensional Decoding Tumor Microenvironment for Immuno-Oncology ResearchPreprint

Zeng, D., Fang, Y., Luo, P., Qiu, W., Wang, S., Shen, R., Gu, W., Huang, X., Mao, Q., Lai, Y.-H., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.01.13.575484 · Cited by 8

Single-cell analysis of human diversity in circulating immune cellsPreprint

Kock, K. H., Tan, L. M., Han, K. Y., Ando, Y., Jevapatarakul, D., Chatterjee, A., Lin, Q. X. X., Buyamin, E. V., Sonthalia, R., Rajagopalan, D., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.06.30.601119 · Cited by 8

Towards the Next Generation of Data‐Driven Therapeutics Using Spatially Resolved Single‐Cell Technologies and Generative AI

Rodov, A., Baniadam, H., Zeiser, R., Amit, I., Yosef, N., Wertheimer, T., & Ingelfinger, F. (2025) · European Journal of Immunology · doi:10.1002/eji.202451234 · Cited by 7

CELLama: Foundation Model for Single Cell and Spatial Transcriptomics by Cell Embedding Leveraging Language Model Abilities

Park, J., Kim, S., Kim, J., Lee, D., Bae, S., Shin, H., Lee, D., & Choi, H. (2025) · Advanced Science · doi:10.1002/advs.202513210 · Cited by 21

Spatially resolved single-cell atlas unveils a distinct cellular signature of fatal lung COVID-19 in a Malawian population

Nyirenda, J., Hardy, O. M., Silva‐Filho, J. L., Herder, V., Attipa, C., Ndovi, C., Siwombo, M., Namalima, T. R., Suwedi-Kapesa, L. C., Ilia, G., et al. (2024) · Nature Medicine · doi:10.1038/s41591-024-03354-3 · Cited by 7

Dynamical systems theory as an organizing principle for single-cell biology

Islam, S., & Bhattacharya, S. (2025) · npj Systems Biology and Applications · doi:10.1038/s41540-025-00565-3 · Cited by 9

CellPhenoX: An Explainable Machine Learning Method for Identifying Cell Phenotypes To Predict Clinical Outcomes from Single‐Cell Multi‐Omics

Young, J., Inamo, J., Caterer, Z., Krishna, R., & Zhang, F. (2025) · Advancement of science · doi:10.1002/advs.202503289 · Cited by 8

Predicting Single-Cell Drug Sensitivity Utilizing Adaptive Weighted Features for Multi-Source Domain Adaptation

Liu, H., Duan, W., & Luo, J. (2025) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2025.3553126 · Cited by 9

Progress on Electro‐Enhancement of Cell Manufacturing

Tian, J. S., & Tay, A. K. P. (2023) · Small Methods · doi:10.1002/smtd.202301281 · Cited by 5

Panpipes: a pipeline for multiomic single-cell and spatial transcriptomic data analysisPreprint

Curion, F., Rich‐Griffin, C., Agarwal, D., Ouologuem, S., Thomas, T. R., Theis, F. J., & Dendrou, C. A. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.03.11.532085 · Cited by 6

Polybacterial intracellular coinfection of epithelial stem cells in periodontitisPreprint

Easter, Q. T., Matuck, B. F., Stark, G. B., Worth, C. L., Predeus, A. V., Fremin, B. J., Huynh, K., Ranganathan, V. N., Pereira, D., Weaver, T. M., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.08.23.554343 · Cited by 6

Mapping and reprogramming human tissue microenvironments with MintFlowPreprint

Akbarnejad, A., Steele, L., Jafree, D. J., Birk, S., Sallese, M. R., Rademaker, K., Boxall, A. R., Rumney, B. M., Tudor, C. L., Patel, M. J., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.06.24.661094 · Cited by 10

PULSAR: a Foundation Model for Multi-scale and Multicellular BiologyPreprint

Pang, K., Rosen, Y., Kedzierska, K., He, Z., Rajagopal, A., Gustafson, C. E., Huynh, G. H., & Leskovec, J. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.11.24.685470 · Cited by 11

Cutting-edge technologies illuminate the neural landscape of cancer: Insights into tumor development

Wang, Y., Wang, Z., Mao, X., Zhang, H., Zhang, L., Yang, Y., Liu, B., Li, X., Luo, F., & Sun, H. (2025) · Cancer Letters · doi:10.1016/j.canlet.2025.217667 · Cited by 5

Encompassing view of spatial and single-cell RNA-seq renews the role of the microvasculature in human atherosclerosisPreprint

Bleckwehl, T., Maryam, S., Babler, A., Nyberg, M., Bosteen, M. H., Halder, M., Pyke, C., Hvid, H., Voetmann, L. M., Sluimer, J. C., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.12.15.571796 · Cited by 5

Systematic mapping of emergent transcriptional states in interacting single-cell dyads by Cell-Cell-seqPreprint

Baghdasarian, S., Wang, Q., Langerman, J., Mao, Z., Wright, H., Gee, C., Cheng, D., McLaughlin, J., Jc, L., Chen, X. T., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.02.05.704136 · Cited by 5

The Human Cell Atlas: Promises, recent developments, and bridging the African single-cell data gap

Abhulimen, E. S. (2024) · African Journal of Laboratory Medicine · doi:10.4102/ajlm.v13i1.2583 · Cited by 4

HCNetlas: A reference database of human cell type-specific gene networks to aid disease genetic analyses

Yu, J., Cha, J., Koh, G., & Lee, I. (2025) · PLoS Biology · doi:10.1371/journal.pbio.3002702 · Cited by 7

Multi-Dimensional Transcriptomics Reveals the Prominent Role of Neuroinflammation in Alzheimer’s Disease

Wang, X., Rong, Z., & Xue, F. (2026) · International Journal of Molecular Sciences · doi:10.3390/ijms27115020 · Cited by 6

TarDis: Achieving robust and structured disentanglement of multiple covariates

İnecik, K., Kara, A., Rose, A., Haniffa, M. A., & Theis, F. J. (2026) · Cell Systems · doi:10.1016/j.cels.2026.101573 · Cited by 5

Research priorities for non-invasive therapies to improve hydrocephalus outcomes

Hochstetler, A., Hehnly, C., Dawes, W. J., Harris, D., Sadegh, C., Mangano, F. T., Lanjewar, S. N., & Chau, M. J. (2025) · Fluids and Barriers of the CNS · doi:10.1186/s12987-025-00632-1 · Cited by 4

hadge: a comprehensive pipeline for donor deconvolution in single cellPreprint

Curion, F., Wu, X., Heumos, L., Gonzales, M., Halle, L., Grant‐Peters, M., Rich‐Griffin, C., Yeung, H., Dendrou, C. A., Schiller, H. B., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.07.23.550061 · Cited by 4

A Single-Cell Bioprinting Method to Reconstruct Native Cellular Microenvironments with Subcellular ResolutionPreprint

Helms, H. R., Oyama, K. A., Davies, A. E., Langer, E. M., & Bertassoni, L. E. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.02.01.578499 · Cited by 4

Label-free single-cell RNA multiplexing leveraging genetic variability

Hoeft, K., Bleckwehl, T., Schumacher, D., Kim, H., Meyer, R., Long, Q., Zhang, L., Möller, C., Clahsen-van Groningen, M. C., Babler, A., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-54270-6 · Cited by 3

Cell and developmental biology: grand challenges

Fisher, A. G. (2024) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2024.1377073 · Cited by 3

A comparative review of single-cell atlases: mapping cellular diversity across species and tissues

Look, K., Goh, P. E., Ming, L. C., Law, S. H., Tan, S. L., Tan, E. W., Ser, H. L., & Goh, B. H. (2025) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-025-05952-x · Cited by 3

Integrative single-cell analysis reveals endothelial diversity in the vasa vasorum of human atherosclerosis

Wu, Y., Xue, Z., Sun, T., Yu, Y., Liang, X., Xing, W., Mu, F., Zhang, Z., Lv, M., Ling, L., et al. (2026) · Communications Biology · doi:10.1038/s42003-026-10095-1 · Cited by 3

scBaseCount: An AI agent-curated, standardized, auto-updated single-cell data repository

Youngblut, N. D., Carpenter, C., Nayebnazar, A., Adduri, A., Shah, R., Ricci-Tam, C., Prashar, J., Ilango, R., Teyssier, N., Konermann, S., et al. (2026) · Cell · doi:10.1016/j.cell.2026.08.025 · Cited by 50

Uncovering intestinal macrophages through the integration of single-cell and spatial transcriptomics

Garrido-Trigo, A., Veny, M., & Salas, A. (2023) · Genes and Immunity · doi:10.1038/s41435-023-00242-7 · Cited by 3

Narrowing Down Key Players in Autoimmunity via Single‐Cell Multiomics

Gjurgjaj, A., & Conde, C. D. (2025) · European Journal of Immunology · doi:10.1002/eji.202451233 · Cited by 5

scX: a user-friendly tool for scRNAseq exploration

Waichman, T. V., Vercesi, M. L., Berardino, A. A., Beckel, M. S., Giacomini, D., Rasetto, N. B., Herrero, M., Bella, D. J. D., Arlotta, P., Schinder, A. F., et al. (2024) · Bioinformatics Advances · doi:10.1093/bioadv/vbae062 · Cited by 3

Single-nucleus RNA and multiomics in situ pairwise sequencing reveals cellular heterogeneity of the abnormal ligamentum teres in patients with developmental dysplasia of the hip

Zhao, Z., Fan, C., Wang, S., Wang, H., Deng, H., Zeng, S., Tang, S., Li, L., Xiong, Z., & Qiu, X. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e27803 · Cited by 3

Multiscale analysis and functional validation of the cellular and genetic determinants of skeletal disease

Chai, R. C. C., Lundberg, M., Freudenthal, B., Smith, J. T., Boughton, A. P., Zhang, Y., Flynn, K. A., Frysz, M., Corr, A. P., Khoo, W. H., et al. (2026) · Nature Genetics · doi:10.1038/s41588-026-02640-9 · Cited by 4

Identification of cell types, states and programs by learning gene set representationsPreprint

Hediyeh-zadeh, S., Whitfield, H. J., Kharbanda, M., Curion, F., Bhuva, D. D., Theis, F. J., & Davis, M. J. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.09.08.556842 · Cited by 3

Immune Monitoring during Cancer Immunotherapy

Shehata, H. M., Dogra, P., & Sanjabi, S. (2024) · Wiley eBooks · doi:10.1002/9781683674023.ch105 · Cited by 3

scTransMIL Bridges Patient-Level Phenotypes and Single-Cell Transcriptomics for Cancer Screening and Heterogeneity InferencePreprint

Tang, Z., Wang, F., Yang, F., Song, J., Chen, C. Y., & Yao, J. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.04.22.649948 · Cited by 3

An AI Agent for cell-type specific brain computer interfacesPreprint

Marin‐Llobet, A., Lin, Z., Baek, J., Aljović, A., Zhang, X., Lee, A. J., Wang, W., Lee, J. Y., Shen, H., He, Y., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.09.11.675660 · Cited by 4

The role of single cell transcriptomics for efficacy and toxicity profiling of chimeric antigen receptor (CAR) T cell therapies

Thomas, M., Brabenec, R., Gregor, L., Andreu-Sanz, D., Carlini, E., Müller, P. J., Gottschlich, A., Simnica, D., Kobold, S., & Marr, C. (2025) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2025.110332 · Cited by 2

The normal human lymph node cell classification and landscape defined by high-dimensional spatial proteomics

Bolognesi, M. M., Dall’Olio, L., Mandelli, G. E., Lorenzi, L., Bosisio, F. M., Haberman, A. M., Bhagat, G., Borghesi, S., Faretta, M., Castellani, G., et al. (2026) · PLOS One · doi:10.1371/journal.pone.0346693 · Cited by 2

Sekwencjonowanie transkryptomu pojedynczych komórek: droga do odkrywania bioróżnorodności komórkowej

Samelak-Czajka, A., Marszałek-Zeńczak, M., & Jackowiak, P. (2024) · Postępy Biochemii · doi:10.18388/pb.2021_532 · Cited by 2

Immune signatures of disease stages and outcomes in myocardial infarction

(2024) · Nature Medicine · doi:10.1038/s41591-024-02954-3 · Cited by 2

Lymphatic System: History, Anatomy, Physiology, Challenges, and Opportunities

Colaco, V., Pokale, R., Mukharya, A., Patel, J. K., Pathak, Y. V., Mutalik, S., Goswami, H. H., & Dhas, N. L. (2024) · Springer eBooks · doi:10.1007/978-3-031-64828-1_1 · Cited by 2

Application of mass cytometry in the immune microenvironment of breast cancer

Shang, Y., Pang, Y., Liu, Y., & Wang, W. (2025) · Medical Oncology · doi:10.1007/s12032-025-02770-w · Cited by 2

Leveraging multiple labeled datasets for the automated annotation of single-cell RNA and ATAC data

Sancho-Zamora, J., Kanhirodan, A., Garrote, X., Rojas, J. M. S., Gevaert, O., Hernáez, M., Serrano, G., & Ochoa, I. (2025) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2025.06.043 · Cited by 2

Multi-Omic Factor Analysis uncovers immunological signatures with pathophysiologic and clinical implications in coronary syndromesPreprint

Pekayvaz, K., Losert, C., Knottenberg, V., van Blokland, I. V., Oelen, R., Groot, H. E., Benjamins, J. W., Brambs, S., Kaiser, R. W. J., Eivers, L., et al. (2023) · medRxiv · doi:10.1101/2023.05.02.23289392 · Cited by 2

A multi-organ map of the human immune system across age, sex and ethnicityPreprint

Mangiola, S., Milton, M., Ranathunga, N., Li-Wai-Suen, C., Odainic, A., Yang, E., Hutchison, W., Garnham, A., Iskander, J., Pal, B., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.06.08.542671 · Cited by 2

CellPhenoX: An eXplainable Cell-specific machine learning method to predict clinical Phenotypes using single-cell multi-omicsPreprint

Young, J., Inamo, J., Caterer, Z., Krishna, R., & Zhang, F. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.01.24.634132 · Cited by 2

A harmonized ovarian cancer scRNA-seq atlas to dissect disease heterogeneity underlying metastatization and chemoresistancePreprint

Sallese, M. R., Aiello, V., Villa, C. E., Riso, P. L., & Testa, G. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.02.11.637633 · Cited by 3

LIBRA: an adaptative integrative tool for paired single‐cell multi‐omics data

Martinez‐de‐Morentin, X., Khan, S. A., Lehmann, R., Qu, S., Maillo, A., Kiani, N. A., Prósper, F., Tegner, J. N., & Gómez-Cabrero, D. (2023) · Quantitative Biology · doi:10.15302/j-qb-022-0318 · Cited by 1

Learning Multi-cellular Representations of Single-Cell Transcriptomics Data Enables Characterization of Patient-Level Disease States

Liu, T., Brouwer, E. D., Kuo, T. C.-Y., Diamant, N., Missarova, A. M., Wang, H., Hao, M., Bravo, H. C., Scalia, G., Regev, A., et al. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-90252-9_27 · Cited by 1

Sketching T cell atlases in the single‐cell era: challenges and recommendations

Bojović, I., Sousa, A. G. G., Junttila, S., & Elo, L. L. (2025) · Immunology and Cell Biology · doi:10.1111/imcb.70040 · Cited by 1

scCAM: An explainable method to annotate scRNA-seq data and identify annotation-related genes based on residual network and layer class activation maps

Zhang, Y., Du, Y., & Fu, Y. (2025) · Gene Reports · doi:10.1016/j.genrep.2025.102297 · Cited by 1

scREPA: Predicting single-cell perturbation responses with cycle-consistent representation alignment

Wang, Y., Chen, X., Li, X., & Wong, K. (2025) · Computational Biology and Chemistry · doi:10.1016/j.compbiolchem.2025.108712 · Cited by 4

Reducing bulky medical images via shape-texture decoupled deep neural networks

Yang, R., Xiao, T., Cheng, Y., & Suo, J. (2026) · Nature Communications · doi:10.1038/s41467-026-68292-9 · Cited by 1

Topography-aware optimal transport for alignment of spatial omics data

Ceccarelli, F., Liò, P., Sáez-Rodríguez, J., Holden, S. B., & Tanevski, J. (2026) · Cell Reports Methods · doi:10.1016/j.crmeth.2026.101373 · Cited by 1

The State of Single-Cell Atlas Data Visualization in the Biological Literature

Keller, M. S., Mörth, E., Smits, T. C., Warchol, S., Guo, G., Wang, Q., Krueger, R., Pfister, H., & Gehlenborg, N. (2025) · IEEE Computer Graphics and Applications · doi:10.1109/mcg.2025.3583979 · Cited by 3

Editorial: Molecular mechanisms regulating phenotypic heterogeneity in human inflammatory diseases

Kapellos, T. S., & Nawijn, M. C. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2023.1214255 · Cited by 1

The Recent Evolution of the Application of Single-Cell Analysis in Kidney Diseases: A bibliometric analysisPreprint

Hun, M., Wen, H., Wen, M., Tian, Q., Wang, Z., Han, P., Vun, T., Som, T., Preap, B., Zhao, M., et al. (2023) · doi:10.22541/au.168620819.99240467/v1 · Cited by 1

Recurrent Composite Markers of Cell Types and StatesPreprint

Li, X., Nguyen, J., & Korkut, A. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.07.17.549344 · Cited by 1

Spatially resolved single-cell atlas of the lung in fatal Covid19 in an African population reveals a distinct cellular signature and an interferon gamma dominated responsePreprint

Nyirenda, J., Hardy, O. M., Silva‐Filho, J. L., Herder, V., Attipa, C., Ndovi, C., Siwombo, M., Namalima, T. R., Suwedi-Kapesa, L. C., Nyasulu, W., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.11.16.566964 · Cited by 1

Protein-based cell population discovery and annotation for CITE-seq data identifies cellular phenotypes associated with critical COVID-19 severityPreprint

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Recreating fibroblast diversity in vitro by activating transcription factors

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Development of an Integrated Single-Cell and Spatial Transcriptomics Atlas of Healthy Human Skin Focusing on the Pilosebaceous UnitPreprint

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Commentary: Toward a global atlas of ocular surface biology: Rationale, design, and clinical applications

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scExplorer: a comprehensive web server for single-cell RNA sequencing data analysis

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Additional file 1 of hadge: a comprehensive pipeline for donor deconvolution in single-cell studies

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Cell Atlases as Roadmaps in Health and Disease

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