Gregory P. Way

9.7k total citations
35 papers, 880 citations indexed

About

Gregory P. Way is a scholar working on Molecular Biology, Biophysics and Media Technology. According to data from OpenAlex, Gregory P. Way has authored 35 papers receiving a total of 880 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Molecular Biology, 10 papers in Biophysics and 5 papers in Media Technology. Recurrent topics in Gregory P. Way's work include Cell Image Analysis Techniques (10 papers), Single-cell and spatial transcriptomics (8 papers) and Image Processing Techniques and Applications (5 papers). Gregory P. Way is often cited by papers focused on Cell Image Analysis Techniques (10 papers), Single-cell and spatial transcriptomics (8 papers) and Image Processing Techniques and Applications (5 papers). Gregory P. Way collaborates with scholars based in United States, Germany and United Kingdom. Gregory P. Way's co-authors include Casey S. Greene, Scott P. McRobert, Nathan Ruhl, Jennifer L. Snekser, Anne E. Carpenter, Shantanu Singh, Jennifer A. Doherty, Chen Wang, Joellen M. Schildkraut and Lauren C. Peres and has published in prestigious journals such as Nature Communications, Scientific Reports and PLoS Biology.

In The Last Decade

Gregory P. Way

31 papers receiving 875 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Gregory P. Way United States	15	438	185	143	105	100	35	880
Serena J. Silver United States	12	1.5k 3.4×	204 1.1×	215 1.5×	158 1.5×	69 0.7×	25	1.9k
Winfried Wiegraebe United States	9	1.1k 2.6×	448 2.4×	95 0.7×	236 2.2×	158 1.6×	11	2.1k
Lauren M. Saunders United States	18	984 2.2×	121 0.7×	134 0.9×	111 1.1×	36 0.4×	27	1.5k
Assaf Zaritsky Israel	16	570 1.3×	140 0.8×	173 1.2×	78 0.7×	14 0.1×	36	1.1k
Thomas Sandmann Germany	20	1.4k 3.3×	58 0.3×	292 2.0×	226 2.2×	292 2.9×	32	2.1k
Abbas Shirinifard United States	17	591 1.3×	57 0.3×	104 0.7×	65 0.6×	21 0.2×	32	1.3k
Silvia Muñoz‐Descalzo United Kingdom	19	1.1k 2.6×	124 0.7×	42 0.3×	67 0.6×	24 0.2×	32	1.3k
Michael J. Lawson United States	13	1.5k 3.4×	313 1.7×	172 1.2×	192 1.8×	21 0.2×	14	1.8k
Leila Mureşan United Kingdom	18	906 2.1×	230 1.2×	50 0.3×	69 0.7×	12 0.1×	47	1.3k
Luis M. Escudero Spain	20	562 1.3×	76 0.4×	43 0.3×	40 0.4×	30 0.3×	52	1.2k

Countries citing papers authored by Gregory P. Way

Since Specialization

Citations

This map shows the geographic impact of Gregory P. Way'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 Gregory P. Way with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gregory P. Way more than expected).

Fields of papers citing papers by Gregory P. Way

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gregory P. Way. 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 Gregory P. Way. The network helps show where Gregory P. Way may publish in the future.

Co-authorship network of co-authors of Gregory P. Way

This figure shows the co-authorship network connecting the top 25 collaborators of Gregory P. Way. A scholar is included among the top collaborators of Gregory P. Way 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 Gregory P. Way. Gregory P. Way 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

Sucharov, Juliana, et al.. (2025). A quadratic paradigm describes the relationship between phenotype severity and variation. Nature Communications. 16(1). 8154–8154.

Mohammadi, Milad, Johannes Knop, Jiamin Huang, et al.. (2025). A morphology and secretome map of pyroptosis. Molecular Biology of the Cell. 36(6). ar63–ar63.

Guzman, Grace, et al.. (2025). High-content microscopy and machine learning characterize a cell morphology signature of NF1 genotype in Schwann cells. 2. 100009–100009.

Kalinin, Alexandr A., John Arévalo, Loan Vulliard, et al.. (2025). A versatile information retrieval framework for evaluating profile strength and similarity. Nature Communications. 16(1). 5181–5181. 2 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

Davidson, Natalie R., Mollie E. Barnard, Amy Campbell, et al.. (2024). Molecular Subtypes of High-Grade Serous Ovarian Cancer across Racial Groups and Gene Expression Platforms. Cancer Epidemiology Biomarkers & Prevention. 33(8). 1114–1125. 4 indexed citations

Berman, Adi Y., David R. Stirling, Beth A. Cimini, et al.. (2023). High-content microscopy reveals a morphological signature of bortezomib resistance. eLife. 12. 7 indexed citations

Way, Gregory P., Heba Sailem, Steven Shave, Richard Kasprowicz, & Neil O. Carragher. (2023). Evolution and impact of high content imaging. SLAS DISCOVERY. 28(7). 292–305. 19 indexed citations

Way, Gregory P., Ted Natoli, Lev Litichevskiy, et al.. (2022). Morphology and gene expression profiling provide complementary information for mapping cell state. Cell Systems. 13(11). 911–923.e9. 55 indexed citations

10.

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

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.

Way, Gregory P., Michael Zietz, Vincent Rubinetti, Daniel Himmelstein, & Casey S. Greene. (2020). Compressing gene expression data using multiple latent space dimensionalities learns complementary biological representations. Genome biology. 21(1). 109–109. 36 indexed citations

13.

Modi, Apexa, Khushbu Patel, Nathan M. Kendsersky, et al.. (2020). Epigenomic profiling of neuroblastoma cell lines. Scientific Data. 7(1). 116–116. 36 indexed citations

14.

Lin, Yu-Hsiu T., Gregory P. Way, Benjamin G. Barwick, et al.. (2019). Integrated phosphoproteomics and transcriptional classifiers reveal hidden RAS signaling dynamics in multiple myeloma. Blood Advances. 3(21). 3214–3227. 14 indexed citations

15.

Chen, Kathleen, et al.. (2018). PathCORE-T: identifying and visualizing globally co-occurring pathways in large transcriptomic compendia. BioData Mining. 11(1). 14–14. 9 indexed citations

16.

Doherty, Jennifer A., Lauren C. Peres, Chen Wang, et al.. (2017). Challenges and Opportunities in Studying the Epidemiology of Ovarian Cancer Subtypes. Current Epidemiology Reports. 4(3). 211–220. 73 indexed citations

17.

Way, Gregory P., Daniel W. Youngstrom, Kurt D. Hankenson, Casey S. Greene, & Struan F.A. Grant. (2017). Implicating candidate genes at GWAS signals by leveraging topologically associating domains. European Journal of Human Genetics. 25(11). 1286–1289. 11 indexed citations

18.

Way, Gregory P., Chen Wang, Habib Hamidi, et al.. (2016). Comprehensive Cross-Population Analysis of High-Grade Serous Ovarian Cancer Supports No More Than Three Subtypes. G3 Genes Genomes Genetics. 6(12). 4097–4103. 26 indexed citations

19.

Way, Gregory P., et al.. (2016). Boldness, Aggression, and Shoaling Assays for Zebrafish Behavioral Syndromes. Journal of Visualized Experiments. 14 indexed citations

20.

Way, Gregory P., et al.. (2015). A Comparison of Methodologies to Test Aggression in Zebrafish. Zebrafish. 12(2). 144–151. 67 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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