Matthew P. Baumgartner

1.3k total citations · 1 hit paper
13 papers, 887 citations indexed

About

Matthew P. Baumgartner is a scholar working on Molecular Biology, Computational Theory and Mathematics and Materials Chemistry. According to data from OpenAlex, Matthew P. Baumgartner has authored 13 papers receiving a total of 887 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 7 papers in Computational Theory and Mathematics and 2 papers in Materials Chemistry. Recurrent topics in Matthew P. Baumgartner's work include Computational Drug Discovery Methods (7 papers), Protein Structure and Dynamics (4 papers) and Machine Learning in Materials Science (2 papers). Matthew P. Baumgartner is often cited by papers focused on Computational Drug Discovery Methods (7 papers), Protein Structure and Dynamics (4 papers) and Machine Learning in Materials Science (2 papers). Matthew P. Baumgartner collaborates with scholars based in United States, United Kingdom and Netherlands. Matthew P. Baumgartner's co-authors include Carlos J. Camacho, David Ryan Koes, David A. Evans, Lewis R. Vidler, Hidde J. Haisma, Nikolaos Eleftheriadis, Thomas E. Smithgall, Rosalina Wisastra, Frank J. Dekker and Jesús Tejero and has published in prestigious journals such as PLoS ONE, Bioorganic & Medicinal Chemistry and Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biology of Lipids.

In The Last Decade

Matthew P. Baumgartner

13 papers receiving 873 citations

Hit Papers

Lessons Learned in Empirical Scoring with smina from the ... 2013 2026 2017 2021 2013 200 400 600
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.

  1. Lessons Learned in Empirical Scoring with smina from the CSAR 2011 Benchmarking Exercise
    2013 741 citations David Ryan Koes, Matthew P. Baumgartner et al. Journal of Chemical Information and Modeling profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Matthew P. Baumgartner United States 9 564 475 180 142 99 13 887
Gabriela Bitencourt‐Ferreira Brazil 17 513 0.9× 458 1.0× 105 0.6× 169 1.2× 67 0.7× 28 907
Tom Oldfield United Kingdom 6 741 1.3× 431 0.9× 178 1.0× 189 1.3× 106 1.1× 8 1.0k
Florian Flachsenberg Germany 12 662 1.2× 541 1.1× 293 1.6× 112 0.8× 111 1.1× 20 1.1k
Sathesh Bhat United States 13 968 1.7× 375 0.8× 163 0.9× 157 1.1× 83 0.8× 21 1.5k
Bruno Bienfait United States 15 639 1.1× 504 1.1× 98 0.5× 122 0.9× 116 1.2× 29 1.1k
Eva Nittinger Sweden 13 543 1.0× 428 0.9× 263 1.5× 92 0.6× 65 0.7× 28 901
Mingyun Shen China 14 687 1.2× 299 0.6× 72 0.4× 166 1.2× 90 0.9× 15 1.0k
Agnes Meyder Germany 10 432 0.8× 316 0.7× 168 0.9× 89 0.6× 76 0.8× 14 752
Michael Baitaluk United States 9 918 1.6× 761 1.6× 177 1.0× 95 0.7× 164 1.7× 11 1.3k

Countries citing papers authored by Matthew P. Baumgartner

Since Specialization
Citations

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

Fields of papers citing papers by Matthew P. Baumgartner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matthew P. Baumgartner

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

All Works

13 of 13 papers shown
1.
Baumgartner, Matthew P. & David A. Evans. (2020). Side chain virtual screening of matched molecular pairs: a PDB-wide and ChEMBL-wide analysis. Journal of Computer-Aided Molecular Design. 34(9). 953–963. 3 indexed citations
2.
Baumgartner, Matthew P., et al.. (2020). Building Admiral, an Automated Molecular Dynamics and Analysis Platform. ACS Medicinal Chemistry Letters. 11(11). 2331–2335. 2 indexed citations
3.
Vidler, Lewis R. & Matthew P. Baumgartner. (2019). Creating a Virtual Assistant for Medicinal Chemistry. ACS Medicinal Chemistry Letters. 10(7). 1051–1055. 9 indexed citations
4.
Chauhan, Bharesh K., Matthew P. Baumgartner, Smaragda Kamakari, et al.. (2018). Case series: Pyramidal cataracts, intact irides and nystagmus from three novel PAX6 mutations. American Journal of Ophthalmology Case Reports. 10. 172–179. 3 indexed citations
5.
Baumgartner, Matthew P. & David A. Evans. (2017). Lessons learned in induced fit docking and metadynamics in the Drug Design Data Resource Grand Challenge 2. Journal of Computer-Aided Molecular Design. 32(1). 45–58. 19 indexed citations
6.
Baumgartner, Matthew P., et al.. (2016). Optimal strategies for virtual screening of induced-fit and flexible target in the 2015 D3R Grand Challenge. Journal of Computer-Aided Molecular Design. 30(9). 695–706. 16 indexed citations
7.
Tejero, Jesús, Alexandr A. Kapralov, Matthew P. Baumgartner, et al.. (2016). Peroxidase activation of cytoglobin by anionic phospholipids: Mechanisms and consequences. Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biology of Lipids. 1861(5). 391–401. 25 indexed citations
8.
Baumgartner, Matthew P.. (2016). IMPROVING RATIONAL DRUG DESIGN BY INCORPORATING NOVEL BIOPHYSICAL INSIGHT. D-Scholarship@Pitt (University of Pittsburgh). 1 indexed citations
9.
Grover, P.L., Haibin Shi, Matthew P. Baumgartner, Carlos J. Camacho, & Thomas E. Smithgall. (2015). Fluorescence Polarization Screening Assays for Small Molecule Allosteric Modulators of ABL Kinase Function. PLoS ONE. 10(7). e0133590–e0133590. 12 indexed citations
10.
Baumgartner, Matthew P. & Carlos J. Camacho. (2015). Choosing the Optimal Rigid Receptor for Docking and Scoring in the CSAR 2013/2014 Experiment. Journal of Chemical Information and Modeling. 56(6). 1004–1012. 17 indexed citations
11.
Moroco, Jamie A., Matthew P. Baumgartner, Hwan Geun Choi, et al.. (2014). A Discovery Strategy for Selective Inhibitors of c‐Src in Complex with the Focal Adhesion Kinase SH3/SH2‐binding Region. Chemical Biology & Drug Design. 86(2). 144–155. 9 indexed citations
12.
Wisastra, Rosalina, Nikolaos Eleftheriadis, Matthew P. Baumgartner, et al.. (2013). Discovery of a novel activator of 5-lipoxygenase from an anacardic acid derived compound collection. Bioorganic & Medicinal Chemistry. 21(24). 7763–7778. 30 indexed citations
13.
Koes, David Ryan, Matthew P. Baumgartner, & Carlos J. Camacho. (2013). Lessons Learned in Empirical Scoring with smina from the CSAR 2011 Benchmarking Exercise. Journal of Chemical Information and Modeling. 53(8). 1893–1904. 741 indexed citations breakdown →

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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