Progress and new challenges in image-based profiling.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος:	Progress and new challenges in image-based profiling.
Συγγραφείς:	Serrano E; Department of Biomedical Informatics, University of Colorado Anschutz, Aurora, CO, USA., Peters J; Morgridge Institute for Research, University of Wisconsin-Madison, Madison, WI, USA., Wagner J; MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom., Graham RE; Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom., Chen Z; Calico Life Sciences, South San Francisco, CA, USA., Feng BY; Calico Life Sciences, South San Francisco, CA, USA., Miranda G; Department of Computational Science and Technology, Science for Life Laboratory, KTH Royal Institute of Technology, Stockholm, Sweden., Kalinin AA; Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA., Vulliard L; Systems Immunology and Single-Cell Biology, German Cancer Research Center (DKFZ), Heidelberg, Germany., Tomkinson J; Department of Biomedical Informatics, University of Colorado Anschutz, Aurora, CO, USA., Mattson C; Department of Biomedical Informatics, University of Colorado Anschutz, Aurora, CO, USA., Lippincott MJ; Department of Biomedical Informatics, University of Colorado Anschutz, Aurora, CO, USA., Kang Z; Research Program in Systems Oncology, University of Helsinki, Helsinki, Finland., Sitani D; Department of Systems Medicine, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany., Bunten D; Department of Biomedical Informatics, University of Colorado Anschutz, Aurora, CO, USA., Seal S; Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA., Carragher NO; Cancer Research UK Scotland Centre, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom., Carpenter AE; Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA., Singh S; Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA., Marin Zapata PA; Bayer AG, Berlin, Germany., Caicedo JC; Morgridge Institute for Research, University of Wisconsin-Madison, Madison, WI, USA., Way GP; Department of Biomedical Informatics, University of Colorado Anschutz, Aurora, CO, USA. gregory.way@cuanschutz.edu.
Πηγή:	Molecular systems biology [Mol Syst Biol] 2026 May; Vol. 22 (5), pp. 624-658. Date of Electronic Publication: 2026 Mar 27.
Τύπος έκδοσης:	Journal Article; Review
Γλώσσα:	English
Στοιχεία περιοδικού:	Publisher: EMBO Press Country of Publication: Germany NLM ID: 101235389 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1744-4292 (Electronic) Linking ISSN: 17444292 NLM ISO Abbreviation: Mol Syst Biol Subsets: MEDLINE
Imprint Name(s):	Publication: 2024- : Heidelberg : EMBO Press Original Publication: London : Nature Pub. Group, c2005-
Ιατρικοί όροι (MeSH):	Image Processing, Computer-Assisted/methods , Computational Biology/methods , Single-Cell Analysis*/methods, Microscopy/methods ; Imaging, Three-Dimensional/methods ; Humans ; Deep Learning ; Software ; Animals ; Phenotype ; Reproducibility of Results
Περίληψη:	For over two decades, image-based profiling has revolutionized cell phenotype analysis. Image-based profiling processes rich, high-throughput, microscopy data into thousands of unbiased measurements that reveal phenotypic patterns powerful for drug discovery, functional genomics, and cell state classification. Here, we review the evolving computational landscape of image-based profiling, detailing the bioinformatics processes involved from feature extraction to normalization and batch correction. We discuss how deep learning has fundamentally reshaped the field. We examine key methodological advancements, such as single-cell analysis, the development of robust similarity metrics, and the expansion into new modalities like optical pooled screening, temporal imaging, and 3D organoid profiling. We also highlight the growth of public benchmarks and open-source software ecosystems as a key driver for fostering reproducibility and collaboration. Despite these advances, the field still faces substantial challenges, particularly in developing methods for emerging temporal and 3D data modalities, establishing robust quality control standards and workflows, and interpreting the processed features. By focusing on the technical evolution of image-based profiling rather than the wide-ranging biological applications, our aim with this review is to provide researchers with a roadmap for navigating the progress and new challenges in this rapidly advancing domain. (© 2026. The Author(s).)
Competing Interests:	Disclosure and competing interests statement. NOC is co-founder, shareholder, and management consultant for PhenoTherapeutics Ltd. SS and AEC serve as scientific advisors for companies that use image-based profiling and Cell Painting (AEC: Recursion, SyzOnc, Quiver Bioscience, SS: Waypoint Bio, Dewpoint Therapeutics, Deepcell) and receive honoraria for occasional scientific visits to pharmaceutical and biotechnology companies. The remaining authors declare no competing interests.
Σχόλια:	Update of: ArXiv. 2025 Aug 7:arXiv:2508.05800v1.. (PMID: 40799808)
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Grant Information:	T15LM009451 HHS \| NIH \| U.S. National Library of Medicine (NLM); 5T15LM007359 HHS \| NIH \| U.S. National Library of Medicine (NLM); R35 GM122547 United States GM NIGMS NIH HHS; RGY0081/2019 Human Frontier Science Program (HFSP); 923014 Gilbert Family Foundation (GFF); 23-28306 Alex's Lemonade Stand Foundation for Childhood Cancer (ALSF); 24CSA1255857 American Heart Association (AHA); DAF2021-225261 Chan Zuckerberg Initiative (CZI); MC_ST_00035 UKRI \| Medical Research Council (MRC); MR/Ro15635/1 UKRI \| Medical Research Council (MRC); 2348683 National Science Foundation (NSF); 10.13039/100014989 Silicon Valley Community Foundation
Contributed Indexing:	Keywords: Cell Profiling; Deep Learning; Feature Extraction; Image-Based Profiling; Phenotypic Screening
Entry Date(s):	Date Created: 20260328 Date Completed: 20260713 Latest Revision: 20260713
Update Code:	20260714
PubMed Central ID:	PMC13144522
DOI:	10.1038/s44320-026-00197-7
PMID:	41896452
Βάση Δεδομένων:	MEDLINE

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ISSN:	1744-4292
DOI:	10.1038/s44320-026-00197-7