Lukas Friedrich

1.7k total citations
25 papers, 940 citations indexed

About

Lukas Friedrich is a scholar working on Computational Theory and Mathematics, Molecular Biology and Pharmacology. According to data from OpenAlex, Lukas Friedrich has authored 25 papers receiving a total of 940 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Computational Theory and Mathematics, 8 papers in Molecular Biology and 8 papers in Pharmacology. Recurrent topics in Lukas Friedrich's work include Computational Drug Discovery Methods (16 papers), Microbial Natural Products and Biosynthesis (6 papers) and Bioactive Compounds and Antitumor Agents (4 papers). Lukas Friedrich is often cited by papers focused on Computational Drug Discovery Methods (16 papers), Microbial Natural Products and Biosynthesis (6 papers) and Bioactive Compounds and Antitumor Agents (4 papers). Lukas Friedrich collaborates with scholars based in Switzerland, Germany and Italy. Lukas Friedrich's co-authors include Gisbert Schneider, Francesca Grisoni, Daniel Merk, Michaël Moret, Daniel Kühn, Stephan A. Sieber, Petra Schneider, Donald Hilvert, Anthony P. Green and Moritz Pott and has published in prestigious journals such as Angewandte Chemie International Edition, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Lukas Friedrich

25 papers receiving 911 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Lukas Friedrich Switzerland 13 574 490 324 124 105 25 940
John W. Mayfield United States 3 581 1.0× 542 1.1× 207 0.6× 102 0.8× 52 0.5× 3 936
Lora Mak United Kingdom 5 836 1.5× 829 1.7× 222 0.7× 179 1.4× 30 0.3× 6 1.2k
A. G. Artemenko Ukraine 19 824 1.4× 444 0.9× 313 1.0× 89 0.7× 95 0.9× 56 1.3k
Ana C. Puhl United States 16 378 0.7× 494 1.0× 165 0.5× 88 0.7× 65 0.6× 48 1.0k
Valery Tkachenko United States 14 450 0.8× 470 1.0× 201 0.6× 45 0.4× 78 0.7× 18 1.0k
Daniel H. Foil United States 18 308 0.5× 276 0.6× 94 0.3× 80 0.6× 47 0.4× 27 797
Jianxin Wang China 20 162 0.3× 515 1.1× 80 0.2× 60 0.5× 38 0.4× 60 1.3k
Enrico Mombelli France 18 309 0.5× 466 1.0× 173 0.5× 28 0.2× 81 0.8× 44 1.1k
Lisa Jeske Germany 5 132 0.2× 998 2.0× 109 0.3× 64 0.5× 201 1.9× 6 1.2k
Eloy Félix United Kingdom 6 625 1.1× 545 1.1× 230 0.7× 88 0.7× 41 0.4× 11 1.0k

Countries citing papers authored by Lukas Friedrich

Since Specialization
Citations

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

Fields of papers citing papers by Lukas Friedrich

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lukas Friedrich

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

All Works

20 of 20 papers shown
1.
Friedrich, Lukas, et al.. (2024). Machine Learning Assisted Hit Prioritization for High Throughput Screening in Drug Discovery. ACS Central Science. 10(4). 823–832. 11 indexed citations
2.
Pekar, Lukas, Thomas L. Clarke, Lukas Friedrich, et al.. (2023). AI/ML combined with next-generation sequencing of VHH immune repertoires enables the rapid identification of de novo humanized and sequence-optimized single domain antibodies: a prospective case study. Frontiers in Molecular Biosciences. 10. 1249247–1249247. 15 indexed citations
3.
Friedrich, Lukas, Sang‐Kyu Park, Peter Ballard, et al.. (2023). Metabolism of (R)‐Praziquantel versus the Activation of a Parasite Transient Receptor Potential Melastatin Ion Channel. ChemMedChem. 18(18). e202300140–e202300140. 5 indexed citations
4.
Grisoni, Francesca, et al.. (2023). Practical guidelines for the use of gradient boosting for molecular property prediction. Journal of Cheminformatics. 15(1). 73–73. 46 indexed citations
5.
Stadler, Eva, Lukas Friedrich, Vandana Thathy, et al.. (2023). Propensity of selecting mutant parasites for the antimalarial drug cabamiquine. Nature Communications. 14(1). 5205–5205. 6 indexed citations
6.
Rusinko, Andrew, et al.. (2023). AIDDISON: Empowering Drug Discovery with AI/ML and CADD Tools in a Secure, Web-Based SaaS Platform. Journal of Chemical Information and Modeling. 64(1). 3–8. 11 indexed citations
7.
Friedrich, Lukas, et al.. (2022). Tuning gradient boosting for imbalanced bioassay modelling with custom loss functions. Journal of Cheminformatics. 14(1). 80–80. 11 indexed citations
8.
Friedrich, Lukas, Claudia M. Rohr, David Maillard, et al.. (2021). Mechanism of Praziquantel Action at a Transient Receptor Potential Channel. Biophysical Journal. 120(3). 336a–336a. 2 indexed citations
9.
Friedrich, Lukas, Gino Cingolani, Ying‐Hui Ko, et al.. (2021). Learning from Nature: From a Marine Natural Product to Synthetic Cyclooxygenase‐1 Inhibitors by Automated De Novo Design. Advanced Science. 8(16). e2100832–e2100832. 20 indexed citations
10.
Friedrich, Lukas, Claudia M. Rohr, Evgeny G. Chulkov, et al.. (2021). Mechanism of praziquantel action at a parasitic flatworm ion channel. Science Translational Medicine. 13(625). eabj5832–eabj5832. 59 indexed citations
11.
Friedrich, Lukas, Ryan Byrne, Inderjeet Singh, et al.. (2020). Shape Similarity by Fractal Dimensionality: An Application in the de novo Design of (−)‐Englerin A Mimetics. ChemMedChem. 15(7). 566–570. 5 indexed citations
12.
Friedrich, Lukas, et al.. (2020). Der Pausenexpress an der Johannes Gutenberg-Universität. 2020(11). 673–675. 11 indexed citations
13.
Pott, Moritz, Richard Obexer, Anthony P. Green, et al.. (2019). Ultrahigh-throughput screening enables efficient single-round oxidase remodelling. Nature Catalysis. 2(9). 740–747. 79 indexed citations
14.
Grisoni, Francesca, Daniel Merk, Lukas Friedrich, & Gisbert Schneider. (2019). Design of Natural‐Product‐Inspired Multitarget Ligands by Machine Learning. ChemMedChem. 14(12). 1129–1134. 28 indexed citations
15.
Merk, Daniel, Francesca Grisoni, Kay Schaller, Lukas Friedrich, & Gisbert Schneider. (2018). Discovery of Novel Molecular Frameworks of Farnesoid X Receptor Modulators by Ensemble Machine Learning. ChemistryOpen. 8(1). 3–3. 4 indexed citations
16.
Merk, Daniel, et al.. (2018). Scaffold hopping from synthetic RXR modulators by virtual screening and de novo design. MedChemComm. 9(8). 1289–1292. 19 indexed citations
17.
Merk, Daniel, et al.. (2018). Computer-Assisted Discovery of Retinoid X Receptor Modulating Natural Products and Isofunctional Mimetics. Journal of Medicinal Chemistry. 61(12). 5442–5447. 40 indexed citations
18.
Merk, Daniel, Lukas Friedrich, Francesca Grisoni, & Gisbert Schneider. (2018). De Novo Design of Bioactive Small Molecules by Artificial Intelligence. Molecular Informatics. 37(1-2). 260 indexed citations
19.
Merk, Daniel, Francesca Grisoni, Lukas Friedrich, & Gisbert Schneider. (2018). Tuning artificial intelligence on the de novo design of natural-product-inspired retinoid X receptor modulators. Communications Chemistry. 1(1). 86 indexed citations
20.
Friedrich, Lukas, Tiago Rodrigues, Claudia S. Neuhaus, Petra Schneider, & Gisbert Schneider. (2016). From Complex Natural Products to Simple Synthetic Mimetics by Computational De Novo Design. Angewandte Chemie International Edition. 55(23). 6789–6792. 38 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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