Andreas Bender

18.5k total citations · 1 hit paper
314 papers, 12.3k citations indexed

About

Andreas Bender is a scholar working on Molecular Biology, Computational Theory and Mathematics and Organic Chemistry. According to data from OpenAlex, Andreas Bender has authored 314 papers receiving a total of 12.3k indexed citations (citations by other indexed papers that have themselves been cited), including 217 papers in Molecular Biology, 196 papers in Computational Theory and Mathematics and 38 papers in Organic Chemistry. Recurrent topics in Andreas Bender's work include Computational Drug Discovery Methods (196 papers), Bioinformatics and Genomic Networks (37 papers) and Metabolomics and Mass Spectrometry Studies (34 papers). Andreas Bender is often cited by papers focused on Computational Drug Discovery Methods (196 papers), Bioinformatics and Genomic Networks (37 papers) and Metabolomics and Mass Spectrometry Studies (34 papers). Andreas Bender collaborates with scholars based in United Kingdom, United States and Netherlands. Andreas Bender's 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 and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Angewandte Chemie International Edition.

In The Last Decade

Andreas Bender

306 papers receiving 12.0k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

DeepSynergy: predicting anti-cancer drug synergy with Deep Learning

2017 382 citations Andreas Bender, Krishna C. Bulusu et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Andreas Bender United Kingdom	61	7.3k	6.9k	2.0k	1.6k	1.5k	314	12.3k
Anne Hersey United Kingdom	31	6.6k 0.9×	6.3k 0.9×	1.8k 0.9×	1.6k 1.0×	1.3k 0.9×	49	11.7k
John P. Overington United Kingdom	41	11.7k 1.6×	6.9k 1.0×	1.5k 0.7×	2.4k 1.5×	1.6k 1.0×	97	16.7k
Tudor I. Oprea United States	68	9.4k 1.3×	6.6k 1.0×	2.3k 1.1×	1.2k 0.8×	1.9k 1.3×	244	18.6k
Dongsheng Cao China	57	6.6k 0.9×	5.7k 0.8×	1.4k 0.7×	2.0k 1.3×	907 0.6×	275	14.6k
Andrew R. Leach United Kingdom	33	9.1k 1.2×	6.9k 1.0×	2.6k 1.3×	2.1k 1.3×	1.5k 1.0×	86	14.8k
Luhua Lai China	61	9.3k 1.3×	5.2k 0.8×	2.2k 1.1×	2.1k 1.3×	1.1k 0.7×	352	15.2k
Benjamin A. Shoemaker United States	28	8.3k 1.1×	4.9k 0.7×	1.0k 0.5×	2.1k 1.3×	1.3k 0.9×	38	14.7k
Anna Gaulton United Kingdom	24	6.9k 0.9×	6.0k 0.9×	949 0.5×	1.5k 0.9×	1.2k 0.8×	37	10.4k
Evan Bolton United States	28	7.3k 1.0×	5.1k 0.7×	1.1k 0.6×	1.6k 1.0×	1.4k 0.9×	71	14.6k

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-authorship network of co-authors of Andreas Bender

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

All Works

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20 of 20 papers shown

Thomas, Morgan, Pierre Matricon, Jonathan S. Mason, et al.. (2025). Identification of nanomolar adenosine A2A receptor ligands using reinforcement learning and structure-based drug design. Nature Communications. 16(1). 5485–5485. 2 indexed citations

Seal, Srijit, et al.. (2024). Graph neural processes for molecules: an evaluation on docking scores and strategies to improve generalization. Journal of Cheminformatics. 16(1). 115–115. 2 indexed citations

Sonabend, Raphael, et al.. (2024). Deep learning for survival analysis: a review. Artificial Intelligence Review. 57(3). 45 indexed citations

Forment, Josep V., Dimitris Polychronopoulos, Andreas Bender, et al.. (2024). Understanding tumour growth variability in breast cancer xenograft models identifies PARP inhibition resistance biomarkers. npj Precision Oncology. 8(1). 266–266. 2 indexed citations

Handa, Koichi, et al.. (2023). On the difficulty of validating molecular generative models realistically: a case study on public and proprietary data. Journal of Cheminformatics. 15(1). 112–112. 9 indexed citations

Seal, Srijit, et al.. (2023). Using chemical and biological data to predict drug toxicity. SLAS DISCOVERY. 28(3). 53–64. 30 indexed citations

Seal, Srijit, Hongbin Yang, Maria‐Anna Trapotsi, et al.. (2023). Merging bioactivity predictions from cell morphology and chemical fingerprint models using similarity to training data. Journal of Cheminformatics. 15(1). 56–56. 19 indexed citations

Mohan, Chakrabhavi Dhananjaya, Muthu K. Shanmugam, Young Yun Jung, et al.. (2023). CXCR4 expression is elevated in TNBC patient derived samples and Z-guggulsterone abrogates tumor progression by targeting CXCL12/CXCR4 signaling axis in preclinical breast cancer model. Environmental Research. 232. 116335–116335. 14 indexed citations

Dziwornu, Godwin Akpeko, Eduard Mas‐Claret, Beverly Egyir, et al.. (2023). Antimicrobial and in silico studies of the triterpenoids of Dichapetalum albidum. Heliyon. 9(7). e18299–e18299. 4 indexed citations

10.

Obrezanova, Olga, Thomas M. Whitehead, Andreas Bender, et al.. (2022). Prediction of In Vivo Pharmacokinetic Parameters and Time–Exposure Curves in Rats Using Machine Learning from the Chemical Structure. Molecular Pharmaceutics. 19(5). 1488–1504. 46 indexed citations

11.

Pandey, Vijay, Xi Zhang, Baocheng Wang, et al.. (2022). Monomerization of Homodimeric Trefoil Factor 3 (TFF3) by an Aminonitrile Compound Inhibits TFF3-Dependent Cancer Cell Survival. ACS Pharmacology & Translational Science. 5(9). 761–773. 11 indexed citations

12.

Módos, Dezső, Padhmanand Sudhakar, Matthew Madgwick, et al.. (2022). A systems genomics approach to uncover patient-specific pathogenic pathways and proteins in ulcerative colitis. Nature Communications. 13(1). 2299–2299. 16 indexed citations

13.

Bender, Andreas & Isidro Cortés‐Ciriano. (2021). Artificial intelligence in drug discovery: what is realistic, what are illusions? Part 2: a discussion of chemical and biological data. Drug Discovery Today. 26(4). 1040–1052. 95 indexed citations

14.

Bender, Andreas & Isidro Cortés‐Ciriano. (2020). Artificial intelligence in drug discovery: what is realistic, what are illusions? Part 1: Ways to make an impact, and why we are not there yet. Drug Discovery Today. 26(2). 511–524. 164 indexed citations

15.

Cortés‐Ciriano, Isidro, Wim Dehaen, Pavel Kříž, et al.. (2020). QSAR-derived affinity fingerprints (part 1): fingerprint construction and modeling performance for similarity searching, bioactivity classification and scaffold hopping. Journal of Cheminformatics. 12(1). 39–39. 27 indexed citations

16.

Cortés‐Ciriano, Isidro, et al.. (2020). QSAR-derived affinity fingerprints (part 2): modeling performance for potency prediction. Journal of Cheminformatics. 12(1). 41–41. 18 indexed citations

17.

Oerton, Erin, et al.. (2018). Developments in toxicogenomics: understanding and predicting compound-induced toxicity from gene expression data. Molecular Omics. 14(4). 218–236. 74 indexed citations

18.

Eastman, Richard T., et al.. (2018). A systematic and prospectively validated approach for identifying synergistic drug combinations against malaria. Malaria Journal. 17(1). 160–160. 16 indexed citations

19.

Módos, Dezső, Krishna C. Bulusu, Dávid Fazekas, et al.. (2017). Neighbours of cancer-related proteins have key influence on pathogenesis and could increase the drug target space for anticancer therapies. npj Systems Biology and Applications. 3(1). 2–2. 20 indexed citations

20.

Isidro‐Llobet, Albert, Agostino Cilibrizzi, James T. Hodgkinson, et al.. (2011). Diversity-oriented synthesis of macrocyclic peptidomimetics. Proceedings of the National Academy of Sciences. 108(17). 6793–6798. 96 indexed citations

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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