Ansgar Schuffenhauer

7.1k total citations · 1 hit paper
56 papers, 4.8k citations indexed

About

Ansgar Schuffenhauer is a scholar working on Computational Theory and Mathematics, Molecular Biology and Pharmacology. According to data from OpenAlex, Ansgar Schuffenhauer has authored 56 papers receiving a total of 4.8k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Computational Theory and Mathematics, 35 papers in Molecular Biology and 14 papers in Pharmacology. Recurrent topics in Ansgar Schuffenhauer's work include Computational Drug Discovery Methods (36 papers), Microbial Natural Products and Biosynthesis (13 papers) and Analytical Chemistry and Chromatography (9 papers). Ansgar Schuffenhauer is often cited by papers focused on Computational Drug Discovery Methods (36 papers), Microbial Natural Products and Biosynthesis (13 papers) and Analytical Chemistry and Chromatography (9 papers). Ansgar Schuffenhauer collaborates with scholars based in Switzerland, Germany and United Kingdom. Ansgar Schuffenhauer's co-authors include Peter Ertl, Edgar Jacoby, Silvio Roggo, Pierre Acklin, Herbert Waldmann, Stefan Wetzel, Peter Willett, Мarcus A. Koch, Khalil Azzaoui and Paul M. Selzer and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and SHILAP Revista de lepidopterología.

In The Last Decade

Ansgar Schuffenhauer

56 papers receiving 4.6k 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.

Estimation of synthetic accessibility score of drug-like molecules based on molecular complexity and fragment contributions

2009 1.1k citations Peter Ertl, Ansgar Schuffenhauer Journal of Cheminformatics profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ansgar Schuffenhauer Switzerland	29	2.9k	2.7k	1.1k	1.0k	855	56	4.8k
Petra Schneider Switzerland	38	2.6k 0.9×	3.1k 1.1×	1.0k 0.9×	996 1.0×	847 1.0×	137	5.9k
W. Patrick Walters United States	27	3.5k 1.2×	3.2k 1.2×	1.1k 0.9×	549 0.5×	1.2k 1.4×	54	5.6k
Humberto González‐Díaz Spain	50	4.6k 1.6×	5.0k 1.8×	1.7k 1.5×	970 0.9×	746 0.9×	276	8.3k
Mark Davies United Kingdom	18	4.7k 1.6×	4.4k 1.6×	706 0.6×	1.0k 1.0×	1.1k 1.3×	44	7.0k
Louisa J. Bellis United Kingdom	10	4.8k 1.6×	4.4k 1.6×	717 0.6×	1000 1.0×	1.2k 1.4×	11	6.7k
Stephen D. Pickett United Kingdom	29	1.9k 0.7×	2.0k 0.7×	1000 0.9×	376 0.4×	670 0.8×	51	4.2k
José L. Medina‐Franco Mexico	51	4.0k 1.4×	5.3k 1.9×	2.0k 1.7×	1.5k 1.5×	698 0.8×	316	8.9k
Valerie J. Gillet United Kingdom	31	2.7k 0.9×	2.0k 0.7×	607 0.5×	396 0.4×	581 0.7×	101	3.7k
Steven L. Dixon United States	27	2.1k 0.7×	2.3k 0.8×	972 0.8×	468 0.5×	470 0.5×	46	4.2k
George Papadatos United Kingdom	19	3.0k 1.0×	3.0k 1.1×	455 0.4×	624 0.6×	793 0.9×	27	4.5k

Countries citing papers authored by Ansgar Schuffenhauer

Since Specialization

Citations

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

Fields of papers citing papers by Ansgar Schuffenhauer

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ansgar Schuffenhauer

This figure shows the co-authorship network connecting the top 25 collaborators of Ansgar Schuffenhauer. A scholar is included among the top collaborators of Ansgar Schuffenhauer 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 Ansgar Schuffenhauer. Ansgar Schuffenhauer 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

Simm, Jaak, Lina Humbeck, Adam Zalewski, et al.. (2021). Splitting chemical structure data sets for federated privacy-preserving machine learning. Journal of Cheminformatics. 13(1). 96–96. 31 indexed citations

Renner, Steffen, Christian Bergsdorf, Rochdi Bouhelal, et al.. (2020). Gene-signature-derived IC50s/EC50s reflect the potency of causative upstream targets and downstream phenotypes. Scientific Reports. 10(1). 9670–9670. 2 indexed citations

Schlapbach, Achim, Láśzló Révész, Carole Pissot‐Soldermann, et al.. (2018). N-aryl-piperidine-4-carboxamides as a novel class of potent inhibitors of MALT1 proteolytic activity. Bioorganic & Medicinal Chemistry Letters. 28(12). 2153–2158. 18 indexed citations

Zhang, Xian, Ansgar Schuffenhauer, Danilo Guerini, et al.. (2017). Identification of SPPL2a Inhibitors by Multiparametric Analysis of a High-Content Ultra-High-Throughput Screen. SLAS DISCOVERY. 22(9). 1106–1119. 9 indexed citations

Wassermann, Anne Mai, Eugen Lounkine, Dominic Hoepfner, et al.. (2015). Dark chemical matter as a promising starting point for drug lead discovery. Nature Chemical Biology. 11(12). 958–966. 104 indexed citations

Kaufmann, Markus, Ansgar Schuffenhauer, Isabelle Fruh, et al.. (2015). High-Throughput Screening Using iPSC-Derived Neuronal Progenitors to Identify Compounds Counteracting Epigenetic Gene Silencing in Fragile X Syndrome. SLAS DISCOVERY. 20(9). 1101–1111. 69 indexed citations

Didiot, Marie-Cécile, Jeffrey Hewett, Thibault Varin, et al.. (2012). Identification of Cardiac Glycoside Molecules as Inhibitors of c-Myc IRES-Mediated Translation. SLAS DISCOVERY. 18(4). 407–419. 22 indexed citations

Schuffenhauer, Ansgar & Thibault Varin. (2011). Rule‐Based Classification of Chemical Structures by Scaffold. Molecular Informatics. 30(8). 646–664. 18 indexed citations

Ertl, Peter, Ansgar Schuffenhauer, & Steffen Renner. (2010). The Scaffold Tree: An Efficient Navigation in the Scaffold Universe. Methods in molecular biology. 672. 245–260. 22 indexed citations

10.

Renner, Steffen, Willem A. L. van Otterlo, Marta Domínguez, et al.. (2009). Bioactivity-guided mapping and navigation of chemical space. Nature Chemical Biology. 5(8). 585–592. 106 indexed citations

11.

Ertl, Peter & Ansgar Schuffenhauer. (2009). Estimation of synthetic accessibility score of drug-like molecules based on molecular complexity and fragment contributions. Journal of Cheminformatics. 1(1). 8–8. 1124 indexed citations breakdown →

12.

Ertl, Peter & Ansgar Schuffenhauer. (2008). Cheminformatics analysis of natural products: Lessons from nature inspiring the design of new drugs. Birkhäuser Basel eBooks. 66. 217–235. 45 indexed citations

13.

Hert, Jérôme, Peter Willett, David J. Wilton, et al.. (2006). New Methods for Ligand-Based Virtual Screening: Use of Data Fusion and Machine Learning to Enhance the Effectiveness of Similarity Searching. Journal of Chemical Information and Modeling. 46(2). 462–470. 167 indexed citations

14.

Ertl, Peter, Stephen Jelfs, Jörg Mühlbacher, Ansgar Schuffenhauer, & Paul M. Selzer. (2006). Quest for the Rings. In Silico Exploration of Ring Universe To Identify Novel Bioactive Heteroaromatic Scaffolds. Journal of Medicinal Chemistry. 49(15). 4568–4573. 205 indexed citations

15.

Jacoby, Edgar, Ansgar Schuffenhauer, Khalil Azzaoui, et al.. (2005). Key Aspects of the Novartis Compound Collection Enhancement Project for the Compilation of a Comprehensive Chemogenomics Drug Discovery Screening Collection. Current Topics in Medicinal Chemistry. 5(4). 397–411. 51 indexed citations

16.

Schopfer, Ulrich, Jan Staněk, M. Girod, et al.. (2005). The Novartis Compound Archive - From Concept to Reality. Combinatorial Chemistry & High Throughput Screening. 8(6). 513–519. 18 indexed citations

17.

Hert, Jérôme, Peter Willett, David J. Wilton, et al.. (2004). Comparison of topological descriptors for similarity-based virtual screening using multiple bioactive reference structures. Organic & Biomolecular Chemistry. 2(22). 3256–3256. 204 indexed citations

18.

Hert, Jérôme, Peter Willett, David J. Wilton, et al.. (2004). Comparison of Fingerprint-Based Methods for Virtual Screening Using Multiple Bioactive Reference Structures. Journal of Chemical Information and Computer Sciences. 44(3). 1177–1185. 239 indexed citations

19.

Schuffenhauer, Ansgar, et al.. (2004). Molecular Diversity Management Strategies for Building and Enhancement of Diverse and Focused Lead Discovery Compound Screening Collections. Combinatorial Chemistry & High Throughput Screening. 7(8). 771–781. 33 indexed citations

20.

Jacoby, Edgar, Ansgar Schuffenhauer, & Philipp Floersheim. (2003). Chemogenomics knowledge-based strategies in drug discovery. Drug News & Perspectives. 16(2). 93–93. 26 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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