Carpenter, Anne E.

Opportunities and obstacles for deep learning in biology and medicine

Ching, T., Himmelstein, D. S., Beaulieu-Jones, B. K., Kalinin, A. A., Do, B. T., Way, G. P., Ferrero, E., Agapow, P.-M., Zietz, M., Hoffman, M. M., et al. (2018) · Journal of The Royal Society Interface

Machine Learning in HealthcareArtificial Intelligence in Healthcare and Education

Cited by 2,310

Cell Painting, a high-content image-based assay for morphological profiling using multiplexed fluorescent dyes

Bray, M.-A., Singh, S., Han, H., Davis, C. T., Borgeson, B., Hartland, C., Kost-Alimova, M., Gustafsdottir, S. M., Gibson, C. C., & Carpenter, A. E. (2016) · Nature Protocols

Cell Image Analysis TechniquesSingle-cell and spatial transcriptomics

Cited by 1,090

Nucleus segmentation across imaging experiments: the 2018 Data Science Bowl

Caicedo, J. C., Goodman, A., Karhohs, K. W., Cimini, B. A., Ackerman, J., Haghighi, M., Heng, C., Becker, T., Doan, M., McQuin, C., et al. (2019) · Nature Methods

Cell Image Analysis TechniquesDigital Imaging for Blood Diseases

Cited by 809

Data-analysis strategies for image-based cell profiling

Caicedo, J. C., Cooper, S., Heigwer, F., Warchal, S., Qiu, P., Molnar, C., Vasilevich, A. S., Barry, J. D., Bansal, H. S., Kraus, O., et al. (2017) · Nature Methods

Cell Image Analysis TechniquesSingle-cell and spatial transcriptomics

Cited by 739

Annotated high-throughput microscopy image sets for validation

Ljosa, V., Sokolnicki, K. L., & Carpenter, A. E. (2012) · Nature Methods

Cell Image Analysis TechniquesDigital Imaging for Blood Diseases

Cited by 601

Multiplex Cytological Profiling Assay to Measure Diverse Cellular States

Gustafsdottir, S. M., Ljosa, V., Sokolnicki, K. L., Anthony Wilson, J., Walpita, D., Kemp, M. M., Petri Seiler, K., Carrel, H. A., Golub, T. R., Schreiber, S. L., et al. (2013) · PLoS ONE

Cell Image Analysis TechniquesComputational Drug Discovery Methods

Cited by 291

nucleAIzer: A Parameter-free Deep Learning Framework for Nucleus Segmentation Using Image Style Transfer

Hollandi, R., Szkalisity, A., Toth, T., Tasnadi, E., Molnar, C., Mathe, B., Grexa, I., Molnar, J., Balind, A., Gorbe, M., et al. (2020) · Cell Systems

Cell Image Analysis TechniquesDigital Imaging for Blood Diseases

Cited by 284

Identification of small molecules for human hepatocyte expansion and iPS differentiation

Shan, J., Schwartz, R. E., Ross, N. T., Logan, D. J., Thomas, D., Duncan, S. A., North, T. E., Goessling, W., Carpenter, A. E., & Bhatia, S. N. (2013) · Nature Chemical Biology

Liver physiology and pathologyPluripotent Stem Cells Research

Cited by 254

Identification of Host-Targeted Small Molecules That Restrict Intracellular Mycobacterium tuberculosis Growth

Stanley, S. A., Barczak, A. K., Silvis, M. R., Luo, S. S., Sogi, K., Vokes, M., Bray, M.-A., Carpenter, A. E., Moore, C. B., Siddiqi, N., et al. (2014) · PLoS Pathogens

Tuberculosis Research and EpidemiologyInfectious Diseases and Tuberculosis

Cited by 251

Human tumors instigate granulin-expressing hematopoietic cells that promote malignancy by activating stromal fibroblasts in mice

Elkabets, M., Gifford, A. M., Scheel, C., Nilsson, B., Reinhardt, F., Bray, M.-A., Carpenter, A. E., Jirström, K., Magnusson, K., Ebert, B. L., et al. (2011) · Journal of Clinical Investigation

Cancer Cells and MetastasisHematopoietic Stem Cell Transplantation

Cited by 201

Toward performance-diverse small-molecule libraries for cell-based phenotypic screening using multiplexed high-dimensional profiling

Wawer, M. J., Li, K., Gustafsdottir, S. M., Ljosa, V., Bodycombe, N. E., Marton, M. A., Sokolnicki, K. L., Bray, M.-A., Kemp, M. M., Winchester, E., et al. (2014) · Proceedings of the National Academy of Sciences

Computational Drug Discovery MethodsCell Image Analysis Techniques

Cited by 196

In vivo HP1 targeting causes large-scale chromatin condensation and enhanced histone lysine methylation

Verschure, P. J., van der Kraan, I., de Leeuw, W., van der Vlag, J., Carpenter, A. E., Belmont, A. S., & van Driel, R. (2005) · Molecular and Cellular Biology

Genomics and Chromatin DynamicsEpigenetics and DNA Methylation

Cited by 183

Optimizing the Cell Painting assay for image-based profiling

Cimini, B. A., Chandrasekaran, S. N., Kost-Alimova, M., Miller, L., Goodale, A., Fritchman, B., Byrne, P., Garg, S., Jamali, N., Logan, D. J., et al. (2023) · Nature Protocols

Cell Image Analysis TechniquesSingle-cell and spatial transcriptomics

Cited by 177

Genetic Architecture of Hsp90-Dependent Drug Resistance

Cowen, L. E., Carpenter, A. E., Matangkasombut, O., Fink, G. R., & Lindquist, S. (2006) · Eukaryotic Cell

Fungal and yeast genetics researchAntifungal resistance and susceptibility

Cited by 159

ZFHX4 Interacts with the NuRD Core Member CHD4 and Regulates the Glioblastoma Tumor-Initiating Cell State

Chudnovsky, Y., Kim, D., Zheng, S., Whyte, W. A., Bansal, M., Bray, M.-A., Gopal, S., Theisen, M. A., Bilodeau, S., Thiru, P., et al. (2014) · Cell Reports

Glioma Diagnosis and TreatmentCancer Cells and Metastasis

Cited by 136

Systematic, multiparametric analysis of Mycobacterium tuberculosis intracellular infection offers insight into coordinated virulence

Barczak, A. K., Avraham, R., Singh, S., Luo, S. S., Zhang, W. R., Bray, M.-A., Hinman, A. E., Thompson, M., Nietupski, R. M., Golas, A., et al. (2017) · PLOS Pathogens

Tuberculosis Research and EpidemiologyMycobacterium research and diagnosis

Cited by 120

Evaluating batch correction methods for image-based cell profiling

Arevalo, J., Su, E., van Dijk, R., Carpenter, A. E., & Singh, S. (2023) · Nature Communications

Single-cell and spatial transcriptomicsCell Image Analysis Techniques

Cited by 89

BIN1 protein isoforms are differentially expressed in astrocytes, neurons, and microglia: neuronal and astrocyte BIN1 are implicated in tau pathology

Taga, M., Petyuk, V. A., White, C., Marsh, G., Ma, Y., Klein, H.-U., Connor, S. M., Kroshilina, A., Yung, C. J., Khairallah, A., et al. (2020) · Molecular Neurodegeneration

Alzheimer's disease research and treatmentsDementia and Cognitive Impairment Research

Cited by 81

Artificial intelligence and cancer

Troyanskaya, O., Trajanoski, Z., Carpenter, A., Thrun, S., Razavian, N., & Oliver, N. (2020) · Nature Cancer

AI in cancer detectionArtificial Intelligence in Healthcare and Education

Cited by 47

Assessing the performance of the Cell Painting assay across different imaging systems

Tromans‐Coia, C., Jamali, N., Abbasi, H. S., Giuliano, K. A., Hagimoto, M., Jan, K., Kaneko, E., Letzsch, S., Schreiner, A., Sexton, J. Z., et al. (2023) · Cytometry Part A

Cell Image Analysis TechniquesSingle-cell and spatial transcriptomics

Cited by 24