Uli Fechner

2.2k citations
18 papers · 1.5k · 1 hit paper · h-index 14

Impact in

Papers in

Uli Fechner

17 papers receiving 1.5k citations

Uli Fechner's Hit Papers

Computer-based de novo design of drug-like molecules 2005 · 632 citations
6320+7+14Years since publication200400600

Peers

Uli Fechner
Comparison fields: 5 of 137
  • Computational Theory and Mathematics 917
  • Molecular Biology 813
  • Spectroscopy 179
  • Pharmacology 75
  • Pharmacology 131
Replace Weifan Zheng with:
Weifan Zheng United States
Christian Lemmen Germany
Nikolaus Stiefl Switzerland
John D. Holliday United Kingdom
Glenn J. Myatt United States
Ian A. Watson United States
Aixia Yan China
Florian Nigsch Switzerland
Burton A. Leland United States
A. Peter Johnson United Kingdom
Uli Fechner relative to Weifan Zheng United States Weifan Zheng's profile →
Citations per field
00.5×1.5×2.4×
Weifan Zheng · 1×
Citations per year

Countries citing papers authored by Uli Fechner

Since Specialization
Citations

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

Fields of papers citing papers by Uli Fechner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 17 scholars most cited alongside Uli Fechner, 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 Uli Fechner Line = papers co-authored together Uli Fechner links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1
Computer-based de novo design of drug-like molecules
Hit paper breakdown →
2005632
2 2003449
3 200485
4 200575
5 200373
6 200744
7 200234
8 200727
9 200719
10 200417
11 200416
12 200616
13 200515
14 200413
15 20136
16 20105
17 20113
18 20140

About Uli Fechner

Uli Fechner is a scholar working on Computational Theory and Mathematics, Molecular Biology, Spectroscopy, Organic Chemistry and Physical and Theoretical Chemistry, having authored 18 papers that have together received 1.5k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (17 papers), Chemical Synthesis and Analysis (6 papers), Analytical Chemistry and Chromatography (4 papers), Click Chemistry and Applications (3 papers), Various Chemistry Research Topics (3 papers), Metabolomics and Mass Spectrometry Studies (3 papers), Molecular spectroscopy and chirality (2 papers) and Machine Learning in Materials Science (2 papers). The work is most often cited by research in Computational Theory and Mathematics (917 citations), Molecular Biology (813 citations), Spectroscopy (179 citations), Pharmacology (75 citations) and Pharmacology (131 citations). Uli Fechner has collaborated with scholars based in Germany, Switzerland and Sweden. Frequent co-authors include Gisbert Schneider, Jens Sadowski, Evgeny Byvatov, Steffen Renner, Petra Schneider, Andreas Schüller, Olivier Roche, Neil Parrott, Ola Engkvist and Ewgenij Proschak. Their work appears in journals such as Journal of Cheminformatics, Journal of Chemical Information and Modeling, Journal of Computer-Aided Molecular Design, Combinatorial Chemistry & High Throughput Screening and PROTEOMICS.

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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