Paul Czodrowski

37 papers receiving 4.1k citations

Hit Papers

Applications of machine learning in drug discovery and development 2019 · 1.7k citations
1.7k200720262013201950010001.5k

Peers

Paul Czodrowski
Comparison fields: 5 of 183
  • Computational Theory and Mathematics 1.3k
  • Health Informatics 92
  • Molecular Biology 2.5k
  • Biophysics 113
  • Materials Chemistry 738
Replace Shanrong Zhao with:
Shanrong Zhao United States
Pedro J. Ballester France
Gerard J. P. van Westen Netherlands
Hongming Chen Sweden
Michaela Spitzer United Kingdom
Kyle Swanson United States
Hao Zhu United States
Oliver Kohlbacher Germany
Parantu K. Shah United States
Michel A. Cuendet Switzerland
Paul Czodrowski relative to Shanrong Zhao United States Shanrong Zhao's profile →
Citations per field
00.5×1.5×1.8×
Shanrong Zhao · 1×
Citations per year

Countries citing papers authored by Paul Czodrowski

Since Specialization
Citations

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

Fields of papers citing papers by Paul Czodrowski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Paul Czodrowski, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Paul Czodrowski Line = papers co-authored together Paul Czodrowski links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20251
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8 20235
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10 202119
11 201952
12
Applications of machine learning in drug discovery and development
Hit paper breakdown →
20191696
13 20182
14 201630
15 201449
16 201421
17 20124
18 20115
19 200941
20 200653

About Paul Czodrowski

Paul Czodrowski is a scholar working on Computational Theory and Mathematics, Biophysics, Filtration and Separation, Molecular Biology and Organic Chemistry, having authored 41 papers that have together received 4.2k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (18 papers), Protein Structure and Dynamics (8 papers), Enzyme Structure and Function (5 papers), Cell Image Analysis Techniques (4 papers), Free Radicals and Antioxidants (4 papers), Protein Kinase Regulation and GTPase Signaling (4 papers), Chemical Reaction Mechanisms (4 papers) and Microbial Natural Products and Biosynthesis (3 papers). The work is most often cited by research in Computational Theory and Mathematics (1.3k citations), Health Informatics (92 citations), Molecular Biology (2.5k citations), Biophysics (113 citations) and Materials Chemistry (738 citations). Paul Czodrowski has collaborated with scholars based in Germany, United States and Switzerland. Frequent co-authors include G. Klebe, Jan H. Jensen, Hui Li, Jens Erik Nielsen, Nathan Baker, Michaela Spitzer, Dominic A. Clark, Jessica Vamathevan, Ian Dunham and George Lee. Their work appears in journals such as Journal of Chemical Information and Modeling, Journal of Medicinal Chemistry, Proteins Structure Function and Bioinformatics, Bioorganic & Medicinal Chemistry Letters and Journal of Cheminformatics.

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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