Markus A. Lill

92 papers receiving 3.5k citations

Markus A. Lill's Hit Papers

Computer-aided drug design platform using PyMOL 2010 · 486 citations
4860+5+10Years since publication100200300400

Peers

Markus A. Lill
Comparison fields: 5 of 153
  • Computational Theory and Mathematics 1.4k
  • Pharmacology 333
  • Molecular Biology 2.0k
  • Biophysics 128
  • Biochemistry 123
Replace Vı́ctor Guallar with:
Vı́ctor Guallar Spain
Kevin Hauser United States
Michael M. Mysinger United States
Jin Huang China
Paul M. Selzer Germany
Káthia M. Honório Brazil
G. Madhavi Sastry India
Lauren Wickstrom United States
Aurélien Grosdidier Switzerland
Michael A. Walters United States
Markus A. Lill relative to Vı́ctor Guallar Spain Vı́ctor Guallar's profile →
Citations per field
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Vı́ctor Guallar · 1×
Citations per year

Countries citing papers authored by Markus A. Lill

Since Specialization
Citations

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

Fields of papers citing papers by Markus A. Lill

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Markus A. Lill. 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 Markus A. Lill. The network helps show where Markus A. Lill may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 95 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Computer-aided drug design platform using PyMOL
Hit paper breakdown →
2010486
2 2021164
3 2008160
4 2015148
5 2005144
6 2011135
7 2020128
8 2007126
9 2002126
10 2013108
11 200997
12 200490
13 201186
14 200181
15 201467
16 201364
17 200659
18 200549
19 202049
20 201447

About Markus A. Lill

Markus A. Lill is a scholar working on Molecular Biology, Computational Theory and Mathematics, Materials Chemistry, Genetics and Spectroscopy, having authored 95 papers that have together received 3.6k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (45 papers), Protein Structure and Dynamics (32 papers), Enzyme Structure and Function (15 papers), Receptor Mechanisms and Signaling (13 papers), Estrogen and related hormone effects (10 papers), Pharmacogenetics and Drug Metabolism (8 papers), Analytical Chemistry and Chromatography (7 papers) and Spectroscopy and Quantum Chemical Studies (7 papers). The work is most often cited by research in Computational Theory and Mathematics (1.4k citations), Pharmacology (333 citations), Molecular Biology (2.0k citations), Biophysics (128 citations) and Biochemistry (123 citations). Markus A. Lill has collaborated with scholars based in United States, Switzerland and Germany. Frequent co-authors include Matthew L. Danielson, Volkhard Helms, Angelo Vedani, Max Dobler, Laura J. Kingsley, Bingjie Hu, Martin Smieško, Gregory L. Wilson, André Fischer and Manuel Sellner. Their work appears in journals such as Journal of Chemical Information and Modeling, Journal of Medicinal Chemistry, The Journal of Chemical Physics, ChemMedChem and Proteins Structure Function and Bioinformatics.

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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