Brice Hoffmann

841 total citations
18 papers, 577 citations indexed

About

Brice Hoffmann is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine and Computational Theory and Mathematics. According to data from OpenAlex, Brice Hoffmann has authored 18 papers receiving a total of 577 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 10 papers in Pulmonary and Respiratory Medicine and 5 papers in Computational Theory and Mathematics. Recurrent topics in Brice Hoffmann's work include Cystic Fibrosis Research Advances (10 papers), Computational Drug Discovery Methods (5 papers) and Advanced biosensing and bioanalysis techniques (5 papers). Brice Hoffmann is often cited by papers focused on Cystic Fibrosis Research Advances (10 papers), Computational Drug Discovery Methods (5 papers) and Advanced biosensing and bioanalysis techniques (5 papers). Brice Hoffmann collaborates with scholars based in France, United Kingdom and United States. Brice Hoffmann's co-authors include Jean‐Philippe Vert, Isabelle Callebaut, Véronique Stoven, Jean‐Paul Mornon, Pierre Lehn, Laurent Jacob, Mikhail Zaslavskiy, Yann Gaston‐Mathé, Didier Rognan and Nicholas G. Martin and has published in prestigious journals such as SHILAP Revista de lepidopterología, Hepatology and Journal of Medicinal Chemistry.

In The Last Decade

Brice Hoffmann

18 papers receiving 571 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Brice Hoffmann France 11 351 208 174 72 60 18 577
Ori Kalid United States 12 513 1.5× 194 0.9× 150 0.9× 15 0.2× 18 0.3× 16 690
Yongping Zhu China 13 247 0.7× 42 0.2× 27 0.2× 14 0.2× 10 0.2× 36 594
Marlet Martínez‐Archundia Mexico 13 335 1.0× 123 0.6× 16 0.1× 22 0.3× 10 0.2× 39 542
Nahlah Makki Almansour Saudi Arabia 13 262 0.7× 48 0.2× 62 0.4× 47 0.7× 13 0.2× 27 565
Matthis Geitmann Sweden 16 507 1.4× 77 0.4× 25 0.1× 13 0.2× 5 0.1× 29 742
Sandra L. Nelson United States 11 210 0.6× 55 0.3× 12 0.1× 23 0.3× 15 0.3× 26 404
Aurelio A. Moya‐García Spain 15 318 0.9× 30 0.1× 16 0.1× 27 0.4× 12 0.2× 30 585
Susmith Mukund United States 11 736 2.1× 49 0.2× 11 0.1× 27 0.4× 9 0.1× 13 1.0k
Jingxing Wu China 5 219 0.6× 143 0.7× 27 0.2× 66 0.9× 9 0.1× 7 487
Hiroshi Tateishi Japan 13 306 0.9× 38 0.2× 29 0.2× 14 0.2× 18 0.3× 91 736

Countries citing papers authored by Brice Hoffmann

Since Specialization
Citations

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

Fields of papers citing papers by Brice Hoffmann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Brice Hoffmann

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

All Works

18 of 18 papers shown
1.
Hoffmann, Brice, et al.. (2024). Drug–Target Interactions Prediction at Scale: The Komet Algorithm with the LCIdb Dataset. Journal of Chemical Information and Modeling. 64(18). 6938–6956. 1 indexed citations
2.
Gaston‐Mathé, Yann, et al.. (2023). Exploring isofunctional molecules: Design of a benchmark and evaluation of prediction performance. Molecular Informatics. 42(4). e2200216–e2200216. 2 indexed citations
3.
Martin, Nicholas G., et al.. (2022). On the Frustration to Predict Binding Affinities from Protein–Ligand Structures with Deep Neural Networks. Journal of Medicinal Chemistry. 65(11). 7946–7958. 108 indexed citations
4.
Boucherle, Benjamin, Arnaud Billet, Brice Hoffmann, et al.. (2020). Targeting different binding sites in the CFTR structures allows to synergistically potentiate channel activity. European Journal of Medicinal Chemistry. 190. 112116–112116. 9 indexed citations
5.
Billet, Arnaud, et al.. (2020). Functional and Pharmacological Characterization of the Rare CFTR Mutation W361R. Frontiers in Pharmacology. 11. 295–295. 6 indexed citations
6.
Boucherle, Benjamin, et al.. (2019). Could we expect new praziquantel derivatives? A meta pharmacometrics/pharmacoinformatics analysis of all antischistosomal praziquantel derivatives found in the literature. SAR and QSAR in environmental research. 30(6). 383–401. 9 indexed citations
7.
Simon, Stéphanie, Natascha Remus, Xavier Decrouy, et al.. (2019). Unsolved severe chronic rhinosinusitis elucidated by extensive CFTR genotyping. SHILAP Revista de lepidopterología. 7(11). 2128–2134. 2 indexed citations
8.
Hoffmann, Brice, Pierre Lehn, Jean‐Luc Décout, et al.. (2018). Combining theoretical and experimental data to decipher CFTR 3D structures and functions. Cellular and Molecular Life Sciences. 75(20). 3829–3855. 21 indexed citations
9.
Callebaut, Isabelle, Brice Hoffmann, & Jean‐Paul Mornon. (2017). The implications of CFTR structural studies for cystic fibrosis drug development. Current Opinion in Pharmacology. 34. 112–118. 12 indexed citations
10.
Martin, Natacha, Nathalie Servel, Bruno Costes, et al.. (2017). Cisvariants identified in F508del complex alleles modulate CFTR channel rescue by small molecules. Human Mutation. 39(4). 506–514. 28 indexed citations
11.
Callebaut, Isabelle, Brice Hoffmann, Pierre Lehn, & Jean‐Paul Mornon. (2016). Molecular modelling and molecular dynamics of CFTR. Cellular and Molecular Life Sciences. 74(1). 3–22. 33 indexed citations
12.
13.
Bonna, Arkadiusz, Grazyna Faure, Tomasz Frączyk, et al.. (2016). New insights into interactions between the nucleotide‐binding domain of CFTR and keratin 8. Protein Science. 26(2). 343–354. 6 indexed citations
14.
Rosay, Thibaut, Alexis Bazire, Thomas Clamens, et al.. (2015). Pseudomonas aeruginosa Expresses a Functional Human Natriuretic Peptide Receptor Ortholog: Involvement in Biofilm Formation. mBio. 6(4). 30 indexed citations
15.
Mornon, Jean‐Paul, Brice Hoffmann, Slavica Jonić, Pierre Lehn, & Isabelle Callebaut. (2014). Full-open and closed CFTR channels, with lateral tunnels from the cytoplasm and an alternative position of the F508 region, as revealed by molecular dynamics. Cellular and Molecular Life Sciences. 72(7). 1377–1403. 70 indexed citations
16.
Hoffmann, Brice, Claude Nespoulous, Hélène Debat, et al.. (2011). Human Genetic Polymorphisms in T1R1 and T1R3 Taste Receptor Subunits Affect Their Function. Chemical Senses. 36(6). 527–537. 50 indexed citations
17.
Hoffmann, Brice, Mikhail Zaslavskiy, Jean‐Philippe Vert, & Véronique Stoven. (2010). A new protein binding pocket similarity measure based on comparison of clouds of atoms in 3D: application to ligand prediction. BMC Bioinformatics. 11(1). 99–99. 70 indexed citations
18.
Jacob, Laurent, Brice Hoffmann, Véronique Stoven, & Jean‐Philippe Vert. (2008). Virtual screening of GPCRs: An in silico chemogenomics approach. BMC Bioinformatics. 9(1). 363–363. 76 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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