Matthew L. Danielson

991 citations
7 papers · 737 indexed · 1 hit paper · h-index 7
Topics
Protein Structure and Dynamics (3 papers)Computational Drug Discovery Methods (3 papers)Pharmacogenetics and Drug Metabolism (2 papers)
Partner nations
United States

In The Last Decade

Matthew L. Danielson

7 papers receiving 726 citations

Hit Papers

Computer-aided drug design platform using PyMOL20102026201520202010100200300400

Peers

Matthew L. Danielson
Comparison fields: 5 of 105
  • Molecular Biology 354
  • Computational Theory and Mathematics 168
  • Organic Chemistry 135
  • Biochemistry 95
  • Surgery 88
Replace Sunhye Hong with:
Sunhye Hong South Korea
Chanin Park South Korea
Katherine Ververis Australia
Ramakrishna Vadde India
Shahzaib Ahamad India
Bader Alshehri Saudi Arabia
Onur Bender Türkiye
Marco Tutone Italy
Federica Moraca Italy
Minky Son South Korea
Matthew L. Danielson relative to Sunhye Hong South Korea Sunhye Hong's profile →
Citations per field
00.5×5.9×
Sunhye Hong · 1×
Citations per year

Countries citing papers authored by Matthew L. Danielson

Since Specialization
Citations

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

Fields of papers citing papers by Matthew L. Danielson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matthew L. Danielson

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

All Works

7 of 7 papers shown
#WorkIndexed citations
1 15
2 20
3 10
4
Computer-aided drug design platform using PyMOLbreakdown →
468
5 14
6 71
7 139

About Matthew L. Danielson

Matthew L. Danielson is a scholar working on Pharmacology, Computational Theory and Mathematics and Biochemistry, having authored 7 papers that have together received 737 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (3 papers), Computational Drug Discovery Methods (3 papers) and Pharmacogenetics and Drug Metabolism (2 papers). The work is most often cited by research in Biochemistry (95 citations), Computational Theory and Mathematics (168 citations) and Pharmacology (54 citations). Matthew L. Danielson has collaborated with scholars based in United States. Frequent co-authors include Markus A. Lill, Qing Jiang, Jianjie Huang, Xinmin Yin, Helene Freiser, Jacob A. Wegelin, Jason A. London, John M. Brock, Daniel P. Link and Wayne L. Monsky. Their work appears in journals such as Proceedings of the National Academy of Sciences, Proteins Structure Function and Bioinformatics and European Journal of Medicinal Chemistry.

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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