Sam Cooper

1.2k total citations
10 papers, 252 citations indexed

About

Sam Cooper is a scholar working on Molecular Biology, Biophysics and Cell Biology. According to data from OpenAlex, Sam Cooper has authored 10 papers receiving a total of 252 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 6 papers in Biophysics and 3 papers in Cell Biology. Recurrent topics in Sam Cooper's work include Cell Image Analysis Techniques (6 papers), Single-cell and spatial transcriptomics (4 papers) and Cellular Mechanics and Interactions (2 papers). Sam Cooper is often cited by papers focused on Cell Image Analysis Techniques (6 papers), Single-cell and spatial transcriptomics (4 papers) and Cellular Mechanics and Interactions (2 papers). Sam Cooper collaborates with scholars based in United Kingdom, United States and Netherlands. Sam Cooper's co-authors include Chris Bakal, Alexis R. Barr, Heba Sailem, Oren Kraus, Alan M Moses, Alex X. Lu, Béla Novák, Frank S. Heldt, Amine Sadok and Robert C. Glen and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Bioinformatics and Molecular Biology of the Cell.

In The Last Decade

Sam Cooper

10 papers receiving 251 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Sam Cooper United Kingdom	7	133	107	72	41	30	10	252
Erin B. Styles Canada	5	204 1.5×	103 1.0×	50 0.7×	9 0.2×	33 1.1×	8	296
Mar Arias-García United Kingdom	7	148 1.1×	99 0.9×	80 1.1×	81 2.0×	17 0.6×	13	337
Ábel Szkalisity Finland	6	203 1.5×	66 0.6×	57 0.8×	11 0.3×	18 0.6×	7	301
Vadim O. Chagin Russia	10	365 2.7×	117 1.1×	29 0.4×	32 0.8×	25 0.8×	19	452
Karthik Damodaran Singapore	5	211 1.6×	61 0.6×	89 1.2×	14 0.3×	9 0.3×	5	281
Jordan Castle United States	6	61 0.5×	54 0.5×	45 0.6×	36 0.9×	9 0.3×	8	181
Dmitry V. Sorokin Russia	10	132 1.0×	116 1.1×	43 0.6×	19 0.5×	40 1.3×	43	298
Julian Mattes Germany	9	71 0.5×	68 0.6×	26 0.4×	24 0.6×	20 0.7×	19	195
Sean M. Gross United States	12	215 1.6×	49 0.5×	35 0.5×	37 0.9×	6 0.2×	23	315
Sandeep Daya United Kingdom	5	142 1.1×	205 1.9×	24 0.3×	12 0.3×	72 2.4×	5	287

Countries citing papers authored by Sam Cooper

Since Specialization

Citations

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

Fields of papers citing papers by Sam Cooper

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sam Cooper. 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 Sam Cooper. The network helps show where Sam Cooper may publish in the future.

Co-authorship network of co-authors of Sam Cooper

This figure shows the co-authorship network connecting the top 25 collaborators of Sam Cooper. A scholar is included among the top collaborators of Sam Cooper 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 Sam Cooper. Sam Cooper is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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10 of 10 papers shown

Lu, Alex X., Oren Kraus, Sam Cooper, & Alan M Moses. (2019). Learning unsupervised feature representations for single cell microscopy images with paired cell inpainting. PLoS Computational Biology. 15(9). e1007348–e1007348. 57 indexed citations

Hoffman, Ann F., John P. Nolan, David F. Gebhard, et al.. (2018). Society of Biomolecular Imaging and Informatics High-Content Screening/High-Content Analysis Emerging Technologies in Biological Models, When and Why?. Assay and Drug Development Technologies. 16(1). 1–6. 3 indexed citations

Heldt, Frank S., Alexis R. Barr, Sam Cooper, Chris Bakal, & Béla Novák. (2018). A comprehensive model for the proliferation–quiescence decision in response to endogenous DNA damage in human cells. Proceedings of the National Academy of Sciences. 115(10). 2532–2537. 62 indexed citations

Cooper, Sam & Chris Bakal. (2017). Accelerating Live Single-Cell Signalling Studies. Trends in biotechnology. 35(5). 422–433. 21 indexed citations

Cooper, Sam, Alexis R. Barr, Robert C. Glen, & Chris Bakal. (2017). NucliTrack: an integrated nuclei tracking application. Bioinformatics. 33(20). 3320–3322. 18 indexed citations

Sailem, Heba, Sam Cooper, & Chris Bakal. (2016). Visualizing quantitative microscopy data: History and challenges. Critical Reviews in Biochemistry and Molecular Biology. 51(2). 96–101. 11 indexed citations

Cooper, Sam, et al.. (2015). Apolar and polar transitions drive the conversion between amoeboid and mesenchymal shapes in melanoma cells. Molecular Biology of the Cell. 26(22). 4163–4170. 23 indexed citations

Sailem, Heba, et al.. (2014). Cross-talk between Rho and Rac GTPases drives deterministic exploration of cellular shape space and morphological heterogeneity. Open Biology. 4(1). 130132–130132. 48 indexed citations

Roberts, Gethin Wyn, et al.. (2002). Look beneath the surface with augmented reality [visualization of subsurface assets]. 13(2). 5 indexed citations

10.

He, Broxmeyer, Ellin Berman, L Juliano, et al.. (1986). Activities derived from established human myeloid cell lines reverse the suppression of cell line colony formation by lactoferrin and transferrin.. PubMed. 14(1). 51–9. 4 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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