Michael E. Pique

35 papers receiving 4.4k citations

Michael E. Pique's Hit Papers

Computational protein–ligand docking and virtual drug screening with the AutoDock suite 2016 · 1.9k citations
1.9k0+7+14Years since publication50010001.5k

Peers

Michael E. Pique
Comparison fields: 5 of 163
  • Endocrinology 286
  • Computational Theory and Mathematics 731
  • Molecular Biology 2.6k
  • Structural Biology 51
  • Microbiology 195
Replace Matteo Dal Peraro with:
Matteo Dal Peraro Switzerland
David W. Rice United Kingdom
Jiye Shi China
Jaroslav Koča Czechia
Sergey Ovchinnikov United States
Elmar Krieger Netherlands
Irene T. Weber United States
Vidyashankara Iyer United States
Taehoon Kim South Korea
Jianyi Yang China
Michael E. Pique relative to Matteo Dal Peraro Switzerland Matteo Dal Peraro's profile →
Citations per field
00.5×5.3×
Matteo Dal Peraro · 1×
Citations per year

Countries citing papers authored by Michael E. Pique

Since Specialization
Citations

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

Fields of papers citing papers by Michael E. Pique

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Michael E. Pique, 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 Michael E. Pique Line = papers co-authored together Michael E. Pique links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Computational protein–ligand docking and virtual drug screening with the AutoDock suite
Hit paper breakdown →
20161871
2
Type IV pilus structure and bacterial pathogenicity
Hit paper breakdown →
2004626
3 2006334
4 2001255
5 2003251
6 2011141
7 1999133
8 1992111
9 199576
10 200774
11 200866
12 198858
13 201356
14 199552
15 198951
16 200748
17 199644
18 197842
19 201640
20 200338

About Michael E. Pique

Michael E. Pique is a scholar working on Molecular Biology, Materials Chemistry, Ecology, Computer Vision and Pattern Recognition and Atomic and Molecular Physics, and Optics, having authored 36 papers that have together received 4.6k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (11 papers), Enzyme Structure and Function (10 papers), Bacteriophages and microbial interactions (5 papers), Force Microscopy Techniques and Applications (4 papers), Computational Drug Discovery Methods (4 papers), DNA Repair Mechanisms (3 papers), Interactive and Immersive Displays (3 papers) and DNA and Nucleic Acid Chemistry (3 papers). The work is most often cited by research in Endocrinology (286 citations), Computational Theory and Mathematics (731 citations), Molecular Biology (2.6k citations), Structural Biology (51 citations) and Microbiology (195 citations). Michael E. Pique has collaborated with scholars based in United States, Canada and Norway. Frequent co-authors include John A. Tainer, Arthur J. Olson, Michel F. Sanner, Stefano Forli, David S. Goodsell, Ruth Huey, Lisa Craig, Victoria A. Roberts, Mark Yeager and A.S. Arvai. Their work appears in journals such as Structure, Molecular Cell, Proteins Structure Function and Bioinformatics, Journal of Biological Chemistry and Nature Reviews Microbiology.

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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