Hans Briem

2.7k total citations
40 papers, 1.4k citations indexed

About

Hans Briem is a scholar working on Molecular Biology, Computational Theory and Mathematics and Oncology. According to data from OpenAlex, Hans Briem has authored 40 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Molecular Biology, 18 papers in Computational Theory and Mathematics and 10 papers in Oncology. Recurrent topics in Hans Briem's work include Computational Drug Discovery Methods (18 papers), Chemical Synthesis and Analysis (11 papers) and Cancer-related Molecular Pathways (6 papers). Hans Briem is often cited by papers focused on Computational Drug Discovery Methods (18 papers), Chemical Synthesis and Analysis (11 papers) and Cancer-related Molecular Pathways (6 papers). Hans Briem collaborates with scholars based in Germany, United States and France. Hans Briem's co-authors include Irwin D. Kuntz, Gerhard Siemeister, Uta Lessel, Martina Schäfer, Matthias Rarey, Andreas Steffen, Ulrich Lücking, Floriane Montanari, Frank Noé and Robin Winter and has published in prestigious journals such as Journal of the American Chemical Society, Cancer Research and Clinical Cancer Research.

In The Last Decade

Hans Briem

38 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hans Briem Germany 22 802 601 393 189 165 40 1.4k
Linli Li China 26 1.2k 1.5× 550 0.9× 444 1.1× 169 0.9× 292 1.8× 111 2.0k
Thompson N. Doman United States 12 831 1.0× 501 0.8× 345 0.9× 153 0.8× 249 1.5× 24 1.5k
Claudio Chuaqui United States 17 1.0k 1.3× 592 1.0× 347 0.9× 137 0.7× 266 1.6× 26 1.4k
Tatu Pantsar Finland 13 947 1.2× 401 0.7× 204 0.5× 168 0.9× 250 1.5× 28 1.6k
Sergio Wong United States 20 889 1.1× 335 0.6× 201 0.5× 187 1.0× 116 0.7× 33 1.3k
James M. Woolven United Kingdom 11 1.3k 1.7× 923 1.5× 443 1.1× 229 1.2× 195 1.2× 13 2.0k
Sathesh Bhat United States 13 968 1.2× 375 0.6× 157 0.4× 163 0.9× 133 0.8× 21 1.5k
Gennadiy Poda United States 16 808 1.0× 665 1.1× 360 0.9× 185 1.0× 230 1.4× 25 1.7k
Konstantin V. Balakin Russia 25 1.0k 1.3× 671 1.1× 579 1.5× 215 1.1× 178 1.1× 95 2.0k
Peter S. Kutchukian United States 19 1.0k 1.3× 377 0.6× 496 1.3× 180 1.0× 127 0.8× 28 1.6k

Countries citing papers authored by Hans Briem

Since Specialization
Citations

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

Fields of papers citing papers by Hans Briem

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hans Briem

This figure shows the co-authorship network connecting the top 25 collaborators of Hans Briem. A scholar is included among the top collaborators of Hans Briem 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 Hans Briem. Hans Briem 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.
Briem, Hans, et al.. (2024). Diversity-oriented multi-compound synthesis optimization. Reaction Chemistry & Engineering. 9(9). 2483–2488.
2.
Mowat, Jeffrey, Rafael Carretero, Gabriele Leder, et al.. (2024). Discovery of BAY-405: An Azaindole-Based MAP4K1 Inhibitor for the Enhancement of T-Cell Immunity against Cancer. Journal of Medicinal Chemistry. 67(19). 17429–17453. 7 indexed citations
3.
Böhnke, Niels, Bård Indrevoll, Stefanie Hammer, et al.. (2023). Mono- and multimeric PSMA-targeting small molecule-thorium-227 conjugates for optimized efficacy and biodistribution in preclinical models. European Journal of Nuclear Medicine and Molecular Imaging. 51(3). 669–680. 9 indexed citations
4.
Briem, Hans, et al.. (2023). Full Modification Control over Retrosynthetic Routes for Guided Optimization of Lead Structures. Journal of Chemical Information and Modeling. 63(21). 6587–6597. 2 indexed citations
5.
Briem, Hans, et al.. (2022). Synthesis-Aware Generation of Structural Analogues. Journal of Chemical Information and Modeling. 62(15). 3565–3576. 12 indexed citations
6.
Lemos, Clara, Volker Schulze, Simon J. Baumgart, et al.. (2021). The potent AMPK inhibitor BAY-3827 shows strong efficacy in androgen-dependent prostate cancer models. Cellular Oncology. 44(3). 581–594. 29 indexed citations
7.
Winter, Robin, Floriane Montanari, Andreas Steffen, et al.. (2019). Efficient multi-objective molecular optimization in a continuous latent space. Chemical Science. 10(34). 8016–8024. 156 indexed citations
8.
Siemeister, Gerhard, Anne Mengel, Amaury E. Fernández‐Montalván, et al.. (2018). Inhibition of BUB1 Kinase by BAY 1816032 Sensitizes Tumor Cells toward Taxanes, ATR, and PARP Inhibitors In Vitro and In Vivo. Clinical Cancer Research. 25(4). 1404–1414. 53 indexed citations
9.
Briem, Hans, et al.. (2017). Computational Macrocyclization: From de novo Macrocycle Generation to Binding Affinity Estimation. ChemMedChem. 12(22). 1866–1872. 23 indexed citations
10.
11.
12.
Schneider, Nadine, Sally Hindle, Gudrun Lange, et al.. (2011). Substantial improvements in large-scale redocking and screening using the novel HYDE scoring function. Journal of Computer-Aided Molecular Design. 26(6). 701–723. 114 indexed citations
13.
Fanghänel, Jörg, Martina Schäfer, Volker Badock, et al.. (2011). A crystallographic fragment screen identifies cinnamic acid derivatives as starting points for potent Pim-1 inhibitors. Acta Crystallographica Section D Biological Crystallography. 67(3). 156–166. 16 indexed citations
14.
Gastreich, Marcus, et al.. (2007). Ultrafast de novo docking combining pharmacophores and combinatorics. Journal of Computer-Aided Molecular Design. 20(12). 717–734. 23 indexed citations
15.
Lücking, Ulrich, Gerhard Siemeister, Martina Schäfer, et al.. (2006). Macrocyclic Aminopyrimidines as Multitarget CDK and VEGF‐R Inhibitors with Potent Antiproliferative Activities. ChemMedChem. 2(1). 63–77. 38 indexed citations
16.
Vedani, Angelo, Hans Briem, Max Dobler, Horst Dollinger, & Daniel R. McMasters. (2000). Multiple-Conformation and Protonation-State Representation in 4D-QSAR:  The Neurokinin-1 Receptor System. Journal of Medicinal Chemistry. 43(23). 4416–4427. 68 indexed citations
17.
Kunz, Horst, Herbert Nar, Herbert Köppen, et al.. (1998). Synthesis of cyclic dipeptide templates, their incorporation into peptides and studies on their conformational and biological properties. Journal of Peptide Research. 51(5). 323–336. 8 indexed citations
18.
Carpy, A., et al.. (1995). Synthesis of a new dipeptide template, its X‐ray structure, and modeling studies on its conformational features. International journal of peptide & protein research. 45(6). 540–546. 4 indexed citations
19.
Höltje, Hans‐Dieter, et al.. (1991). Neue Erkenntnisse über molekulare Wirkungsmechanismen von Arzneistoffen. Pharmazie in unserer Zeit. 20(2). 59–63. 1 indexed citations
20.
Sveinbjörnsdóttir, Sigurlaug, Sanna Gudmundsson, & Hans Briem. (1991). Oropharyngeal colonization in the elderly. European Journal of Clinical Microbiology & Infectious Diseases. 10(11). 959–963. 20 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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