David B. Ascher

19.9k citations
187 papers · 11.8k indexed · 7 hit papers · h-index 46

Impact in

Papers in

David B. Ascher

181 papers receiving 11.7k citations

Hit Papers

Deep-PK: deep learning for small molecule pharmacokinetic and toxicity prediction 2024 · 91 citations
91201320262017202110002.0k3.0k

Peers

David B. Ascher
Comparison fields: 5 of 174
  • Computational Theory and Mathematics 2.6k
  • Molecular Biology 6.9k
  • Infectious Diseases 1.4k
  • Pharmacology 555
  • Toxicology 208
Replace Douglas E. V. Pires with:
Douglas E. V. Pires Australia
Anton Simeonov United States
Jason K. Perry United States
Md. Imtaiyaz Hassan India
Jeremy R. Greenwood United States
Andrew D. Mesecar United States
Stefano Forli United States
Leah L. Frye United States
Kaixian Chen China
Robert Preißner Germany
David B. Ascher relative to Douglas E. V. Pires Australia Douglas E. V. Pires's profile →
Citations per field
00.5×1.7×
Douglas E. V. Pires · 1×
Citations per year

Countries citing papers authored by David B. Ascher

Since Specialization
Citations

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

Fields of papers citing papers by David B. Ascher

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David B. Ascher. 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 David B. Ascher. The network helps show where David B. Ascher may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20241
3 20244
4 20241
5
DDMut: predicting effects of mutations on protein stability using deep learning
Hit paper breakdown →
2023100
6 202337
7 202310
8 202223
9 202111
10 202114
11 202040
12 201951
13 201924
14 201868
15 201838
16 201831
17 201824
18 2017140
19 201790
20 201748

About David B. Ascher

David B. Ascher is a scholar working on Computational Theory and Mathematics, Molecular Biology, Infectious Diseases, Virology and Molecular Medicine, having authored 187 papers that have together received 11.8k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (36 papers), Computational Drug Discovery Methods (33 papers), RNA and protein synthesis mechanisms (24 papers), Bioinformatics and Genomic Networks (16 papers), Genomics and Rare Diseases (14 papers), Biochemical and Molecular Research (14 papers), Tuberculosis Research and Epidemiology (13 papers) and Enzyme Structure and Function (12 papers). The work is most often cited by research in Computational Theory and Mathematics (2.6k citations), Molecular Biology (6.9k citations), Infectious Diseases (1.4k citations), Pharmacology (555 citations) and Toxicology (208 citations). David B. Ascher has collaborated with scholars based in Australia, United Kingdom and Brazil. Frequent co-authors include Douglas E. V. Pires, Tom L. Blundell, Carlos H. M. Rodrigues, T.L. Blundell, Yoochan Myung, Bernardo Ochoa‐Montaño, Arun Prasad Pandurangan, Harry Jubb, Michael W. Parker and Lisa M. Kaminskas. Their work appears in journals such as Nucleic Acids Research, Briefings in Bioinformatics, Scientific Reports, Protein Science and Computational and Structural Biotechnology Journal.

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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