Anne E. Carpenter

37.3k total citations · 8 hit papers
166 papers, 19.8k citations indexed

About

Anne E. Carpenter is a scholar working on Biophysics, Molecular Biology and Media Technology. According to data from OpenAlex, Anne E. Carpenter has authored 166 papers receiving a total of 19.8k indexed citations (citations by other indexed papers that have themselves been cited), including 103 papers in Biophysics, 101 papers in Molecular Biology and 37 papers in Media Technology. Recurrent topics in Anne E. Carpenter's work include Cell Image Analysis Techniques (101 papers), Single-cell and spatial transcriptomics (41 papers) and Advanced Fluorescence Microscopy Techniques (39 papers). Anne E. Carpenter is often cited by papers focused on Cell Image Analysis Techniques (101 papers), Single-cell and spatial transcriptomics (41 papers) and Advanced Fluorescence Microscopy Techniques (39 papers). Anne E. Carpenter collaborates with scholars based in United States, United Kingdom and Germany. Anne E. Carpenter's co-authors include David M. Sabatini, Michael R. Lamprecht, Thouis R. Jones, David A. Guertin, Jason Moffat, Polina Golland, Shantanu Singh, Robert A. Lindquist, Allen Goodman and Ola Friman and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.

In The Last Decade

Anne E. Carpenter

161 papers receiving 19.6k citations

Hit Papers

5 papers align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

CellProfiler: image analysis software for identifying and quantifying cell phenotypes

2006 3.8k citations Anne E. Carpenter et al. profile →
A Lentiviral RNAi Library for Human and Mouse Genes Applied to an Arrayed Viral High-Content Screen

2006 1.4k citations Anne E. Carpenter, William C. Hahn et al. profile →
CellProfiler 3.0: Next-generation image processing for biology

2018 1.2k citations Claire McQuin, Allen Goodman et al. PLoS Biology profile →
mTOR Complex 1 Regulates Lipin 1 Localization to Control the SREBP Pathway

2011 965 citations Anne E. Carpenter et al. profile →
CellProfiler 4: improvements in speed, utility and usability

2021 960 citations Anne E. Carpenter, Beth A. Cimini et al. profile →
Improved structure, function and compatibility for CellProfiler: modular high-throughput image analysis software

2011 765 citations Lee Kamentsky, Adam Fraser et al. Bioinformatics profile →
CellProfiler™: Free, Versatile Software for Automated Biological Image Analysis

2007 686 citations Anne E. Carpenter et al. profile →
Nucleus segmentation across imaging experiments: the 2018 Data Science Bowl

2019 463 citations Juan C. Caicedo, Allen Goodman et al. Nature Methods profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Anne E. Carpenter United States	58	11.0k	6.2k	2.2k	2.1k	1.8k	166	19.8k
Jason Moffat Canada	56	11.9k 1.1×	1.9k 0.3×	992 0.5×	2.0k 1.0×	478 0.3×	168	16.3k
Michael R. Lamprecht United States	10	10.3k 0.9×	1.8k 0.3×	1.4k 0.6×	1.1k 0.5×	476 0.3×	14	17.9k
Jean‐Christophe Olivo‐Marín France	53	4.2k 0.4×	2.2k 0.4×	1.0k 0.5×	1.4k 0.6×	738 0.4×	224	10.7k
Jan Ellenberg Germany	80	16.6k 1.5×	3.4k 0.6×	1.0k 0.5×	5.9k 2.8×	338 0.2×	180	21.3k
Thouis R. Jones United States	22	3.7k 0.3×	2.2k 0.4×	677 0.3×	798 0.4×	1.6k 0.9×	36	9.3k
Roland Eils Germany	68	14.5k 1.3×	1.4k 0.2×	1.1k 0.5×	1.6k 0.8×	239 0.1×	346	25.1k
David A. Guertin United States	39	14.8k 1.3×	1.4k 0.2×	577 0.3×	2.7k 1.3×	374 0.2×	63	21.2k
Gaudenz Danuser United States	71	8.2k 0.8×	3.1k 0.5×	3.2k 1.5×	9.9k 4.7×	276 0.2×	210	17.7k
Qingming Luo China	62	3.5k 0.3×	2.9k 0.5×	4.6k 2.1×	389 0.2×	439 0.2×	560	14.6k
Robert A. Lindquist United States	10	4.8k 0.4×	1.5k 0.2×	477 0.2×	1.3k 0.6×	420 0.2×	10	7.5k

Countries citing papers authored by Anne E. Carpenter

Since Specialization

Citations

This map shows the geographic impact of Anne E. Carpenter's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Anne E. Carpenter with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anne E. Carpenter more than expected).

Fields of papers citing papers by Anne E. Carpenter

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Anne E. Carpenter. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Anne E. Carpenter. The network helps show where Anne E. Carpenter may publish in the future.

Co-authorship network of co-authors of Anne E. Carpenter

This figure shows the co-authorship network connecting the top 25 collaborators of Anne E. Carpenter. A scholar is included among the top collaborators of Anne E. Carpenter based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Anne E. Carpenter. Anne E. Carpenter is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Rouquié, David, Andreas Bender, Jaime H. Cheah, et al.. (2025). The OASIS Consortium: integrating multi-omics technologies to transform chemical safety assessment. Toxicological Sciences. 208(2). 225–232. 1 indexed citations

Tegtmeyer, Matthew, Jatin Arora, Samira Asgari, et al.. (2024). High-dimensional phenotyping to define the genetic basis of cellular morphology. Nature Communications. 15(1). 347–347. 21 indexed citations

Arévalo, John, et al.. (2024). Evaluating batch correction methods for image-based cell profiling. Nature Communications. 15(1). 6516–6516. 19 indexed citations

Seal, Srijit, Jordi Carreras‐Puigvert, Shantanu Singh, et al.. (2024). From pixels to phenotypes: Integrating image-based profiling with cell health data as BioMorph features improves interpretability. Molecular Biology of the Cell. 35(3). mr2–mr2. 9 indexed citations

Berryer, Martin H., Gizem Rizki, Kristina M. Holton, et al.. (2023). High-content synaptic phenotyping in human cellular models reveals a role for BET proteins in synapse assembly. eLife. 12. 5 indexed citations

Carpenter, Anne E., Beth A. Cimini, & Kevin W. Eliceiri. (2023). Smart microscopes of the future. Nature Methods. 20(7). 962–964. 15 indexed citations

Haghighi, Marzieh, Mário Costa Cruz, Erin Weisbart, et al.. (2023). Pseudo-Labeling Enhanced by Privileged Information and Its Application to In Situ Sequencing Images. 4775–4784. 1 indexed citations

Moshkov, Nikita, Tim Becker, Kevin Yang, et al.. (2023). Predicting compound activity from phenotypic profiles and chemical structures. Nature Communications. 14(1). 1967–1967. 40 indexed citations

Way, Gregory P., Maria Kost‐Alimova, Tsukasa Shibue, et al.. (2021). Predicting cell health phenotypes using image-based morphology profiling. Molecular Biology of the Cell. 32(9). 995–1005. 77 indexed citations

10.

Tomov, Martin L., Alison O’Neil, Hamdah Shafqat Abbasi, et al.. (2021). Resolving cell state in iPSC-derived human neural samples with multiplexed fluorescence imaging. Communications Biology. 4(1). 786–786. 8 indexed citations

11.

Way, Gregory P., Casey S. Greene, Piero Carninci, et al.. (2021). A field guide to cultivating computational biology. PLoS Biology. 19(10). e3001419–e3001419. 11 indexed citations

12.

Doan, Minh, Juan Carlos Caicedo, Stefanie Siegert, et al.. (2020). Objective assessment of stored blood quality by deep learning. Proceedings of the National Academy of Sciences. 117(35). 21381–21390. 67 indexed citations

13.

Rohban, Mohammad Hossein, Hamdah Shafqat Abbasi, Shantanu Singh, & Anne E. Carpenter. (2019). Capturing single-cell heterogeneity via data fusion improves image-based profiling. Nature Communications. 10(1). 26 indexed citations

14.

Rueden, Curtis, Ellen T. Arena, Jan Eglinger, et al.. (2019). Scientific Community Image Forum: A discussion forum for scientific image software. PLoS Biology. 17(6). e3000340–e3000340. 25 indexed citations

15.

Doan, Minh, Marian Case, Dino Mašić, et al.. (2017). Label-Free Analyses of Minimal Residual Disease in ALL Using Deep Learning and Imaging Flow Cytometry. Blood. 130. 1437–1437. 2 indexed citations

16.

Dao, David, Adam Fraser, Jane Hung, et al.. (2016). CellProfiler Analyst: interactive data exploration, analysis and classification of large biological image sets. Bioinformatics. 32(20). 3210–3212. 87 indexed citations

17.

Jolly, Amber L., Chi‐Hao Luan, Sara F. Dunne, et al.. (2016). A Genome-wide RNAi Screen for Microtubule Bundle Formation and Lysosome Motility Regulation in Drosophila S2 Cells. Cell Reports. 14(3). 611–620. 5 indexed citations

18.

Metelo, Ana M., Xiang Li, Youngnam N. Jin, et al.. (2015). Pharmacological HIF2α inhibition improves VHL disease–associated phenotypes in zebrafish model. Journal of Clinical Investigation. 125(5). 1987–1997. 38 indexed citations

19.

Du, Ziming, Malak Abedalthagafi, Ayal A. Aizer, et al.. (2014). Increased expression of the immune modulatory molecule PD-L1 (CD274) in anaplastic meningioma. Oncotarget. 6(7). 4704–4716. 126 indexed citations

20.

Cataldo, Anne M., Donna L. McPhie, Nicholas T. Lange, et al.. (2010). Abnormalities in Mitochondrial Structure in Cells from Patients with Bipolar Disorder. American Journal Of Pathology. 177(2). 575–585. 196 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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