Nicole E. Bodycombe

3.9k total citations
9 papers, 677 citations indexed

About

Nicole E. Bodycombe is a scholar working on Molecular Biology, Computational Theory and Mathematics and Biophysics. According to data from OpenAlex, Nicole E. Bodycombe has authored 9 papers receiving a total of 677 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 5 papers in Computational Theory and Mathematics and 3 papers in Biophysics. Recurrent topics in Nicole E. Bodycombe's work include Computational Drug Discovery Methods (5 papers), Cell Image Analysis Techniques (3 papers) and Advanced Biosensing Techniques and Applications (2 papers). Nicole E. Bodycombe is often cited by papers focused on Computational Drug Discovery Methods (5 papers), Cell Image Analysis Techniques (3 papers) and Advanced Biosensing Techniques and Applications (2 papers). Nicole E. Bodycombe collaborates with scholars based in United States, Slovakia and Austria. Nicole E. Bodycombe's co-authors include Stuart L. Schreiber, Paul A. Clemons, Alykhan F. Shamji, Bridget K. Wagner, Joshua Wilson, Angela N. Koehler, Kathleen Petri Seiler, Martha Lucía Serrano, Nicola Tolliday and J. P. Sullivan and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Bioinformatics.

In The Last Decade

Nicole E. Bodycombe

9 papers receiving 659 citations

Peers

Nicole E. Bodycombe

MB

CTM

OC

PHARM

BIOPH

Vladimir Chupakhin Russia

Mathias J. Wawer Germany

Lewis Mervin United Kingdom

Tuomo Kalliokoski Finland

Matthew P. Baumgartner United States

Filip Miljković Germany

Peter Monecke Germany

Michael Reutlinger Switzerland

Sanna Niinivehmas Finland

Fangjin Chen China

Vladimir Chupakhin Russia

Nicole E. Bodycombe

319 ×0.7

MB

301 ×1.0

CTM

84 ×0.5

OC

61 ×0.5

PHARM

101 ×1.0

BIOPH

Citations per year, relative to Nicole E. Bodycombe Nicole E. Bodycombe (= 1×) peers Vladimir Chupakhin

Countries citing papers authored by Nicole E. Bodycombe

Since Specialization

Citations

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

Fields of papers citing papers by Nicole E. Bodycombe

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nicole E. Bodycombe. 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 Nicole E. Bodycombe. The network helps show where Nicole E. Bodycombe may publish in the future.

Co-authorship network of co-authors of Nicole E. Bodycombe

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

All Works

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9 of 9 papers shown

1.

Zhang, Fan, Nicole E. Bodycombe, Eric T. Wang, et al.. (2017). A flow cytometry-based screen identifies MBNL1 modulators that rescue splicing defects in myotonic dystrophy type I. Human Molecular Genetics. 26(16). 3056–3068. 29 indexed citations

2.

Bray, Mark‐Anthony, Sigrun Gustafsdottir, Mohammad Hossein Rohban, et al.. (2017). A dataset of images and morphological profiles of 30 000 small-molecule treatments using the Cell Painting assay. GigaScience. 6(12). 1–5. 110 indexed citations

3.

Dančík, Vlado, Nicole E. Bodycombe, Kathleen Petri Seiler, et al.. (2014). Connecting Small Molecules with Similar Assay Performance Profiles Leads to New Biological Hypotheses. SLAS DISCOVERY. 19(5). 771–781. 20 indexed citations

4.

Seiler, Kathleen Petri, et al.. (2011). Master Data Management: Getting your House in Order. Combinatorial Chemistry & High Throughput Screening. 14(9). 749–756. 2 indexed citations

5.

Swamidass, S. Joshua, et al.. (2011). Utility-Aware Screening with Clique-Oriented Prioritization. Journal of Chemical Information and Modeling. 52(1). 29–37. 5 indexed citations

6.

Swamidass, S. Joshua, et al.. (2011). Enhancing the rate of scaffold discovery with diversity-oriented prioritization. Bioinformatics. 27(16). 2271–2278. 8 indexed citations

7.

Clemons, Paul A., Nicole E. Bodycombe, Joshua Wilson, et al.. (2010). Small molecules of different origins have distinct distributions of structural complexity that correlate with protein-binding profiles. Proceedings of the National Academy of Sciences. 107(44). 18787–18792. 280 indexed citations

8.

Swamidass, S. Joshua, Joshua A. Bittker, Nicole E. Bodycombe, Seán Ryder, & Paul A. Clemons. (2010). An Economic Framework to Prioritize Confirmatory Tests after a High-Throughput Screen. SLAS DISCOVERY. 15(6). 680–686. 13 indexed citations

9.

Seiler, Kathleen Petri, Grinson George, Mary Pat Happ, et al.. (2007). ChemBank: a small-molecule screening and cheminformatics resource database. Nucleic Acids Research. 36(Database). D351–D359. 210 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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