Andreas Bender

306 papers receiving 12.0k citations

Hit Papers

DeepSynergy: predicting anti-cancer drug synergy with Deep Learning 2017 · 382 citations
3822017202620202023100200300

Peers

Andreas Bender
Comparison fields: 5 of 194
  • Computational Theory and Mathematics 6.9k
  • Pharmacology 1.1k
  • Biophysics 716
  • Molecular Biology 7.3k
  • Pharmacology 1.5k
Replace Dongsheng Cao with:
Dongsheng Cao China
Tudor I. Oprea United States
John P. Overington United Kingdom
Luhua Lai China
Jürgen Bajorath Germany
Gisbert Schneider Switzerland
Anne Hersey United Kingdom
Yu Chen China
John J. Irwin United States
Andrew R. Leach United Kingdom
Andreas Bender relative to Dongsheng Cao China Dongsheng Cao's profile →
Citations per field
00.5×1.5×2.3×
Dongsheng Cao · 1×
Citations per year

Countries citing papers authored by Andreas Bender

Since Specialization
Citations

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

Fields of papers citing papers by Andreas Bender

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 314 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004450
2
DeepSynergy: predicting anti-cancer drug synergy with Deep Learning
Hit paper breakdown →
2017382
3 2012317
4 2007266
5 2004254
6 2007247
7 2008240
8 2009229
9 2009221
10 2012217
11 2011204
12 2003202
13 2020164
14 2014149
15 2005146
16 2006140
17 2006140
18 2015138
19 2006136
20 2010131

About Andreas Bender

Andreas Bender is a scholar working on Computational Theory and Mathematics, Biophysics, Pharmacology, Molecular Biology and Pharmacology, having authored 314 papers that have together received 12.3k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (196 papers), Bioinformatics and Genomic Networks (37 papers), Machine Learning in Materials Science (34 papers), Metabolomics and Mass Spectrometry Studies (34 papers), Protein Structure and Dynamics (29 papers), Chemical Synthesis and Analysis (28 papers), Microbial Natural Products and Biosynthesis (27 papers) and Cell Image Analysis Techniques (25 papers). The work is most often cited by research in Computational Theory and Mathematics (6.9k citations), Pharmacology (1.1k citations), Biophysics (716 citations), Molecular Biology (7.3k citations) and Pharmacology (1.5k citations). Andreas Bender has collaborated with scholars based in United Kingdom, United States and Netherlands. Frequent co-authors include Robert C. Glen, Isidro Cortés‐Ciriano, Jeremy L. Jenkins, John W. Davies, Meir Glick, David R. Spring, Hamse Y. Mussa, Adriaan P. IJzerman, Gerard J. P. van Westen and Stephan Reiling. Their work appears in journals such as Journal of Chemical Information and Modeling, Journal of Cheminformatics, Journal of Medicinal Chemistry, PLoS ONE and Chemical Research in Toxicology.

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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