Didier Rognan
Computational Theory and Mathematics · 2000–2022
A researcher in the Science corpus: 4 papers; trusts 3 researchers and is trusted by 9 researchers here, as inferred from the citation graph.
Subfields
- Computational Theory and Mathematics — 49 citations into it; #5,043 of 12,182 by trust here, #616 by citations
- Molecular Biology — 39 citations into it; #5,967 of 17,773 by trust here, #4,474 by citations
- Organic Chemistry — 13 citations into it; #390 of 1,495 by trust here, #437 by citations
- Radiology, Nuclear Medicine and Imaging — 9 citations into it
- Spectroscopy — 5 citations into it
Whom Didier Rognan trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Who trusts Didier Rognan overall
Papers from Didier Rognan's perspective
Ordered by how strongly the researchers Didier Rognan trusts endorse each paper. Same corpus, a different order for every researcher.
- Consensus scoring: A method for obtaining improved hit rates from docking databases of three-dimensional structures into proteins.
- Consensus scoring for ligand/protein interactions. (Journal of Molecular Graphics and Modelling)
- EUDOC: a computer program for identification of drug interaction sites in macromolecules and drug leads from chemical databases
- Gaussian docking functions. (Biopolymers)
- Detailed analysis of scoring functions for virtual screening. (Journal of Medicinal Chemistry)
- Flexible docking using tabu search and an empirical estimate of binding affinity
- Molecular recognition and docking algorithms.
- The Protein Data Bank: a computer-based archival file for macromolecular structures.
- A new test set for validating predictions of protein–ligand interaction (Proteins: Structure, Function, and Bioinformatics)
- A general and fast scoring function for protein-ligand interactions: a simplified potential approach.
Their papers
- Protein-based virtual screening of chemical databases. 1. Evaluation of different docking/scoring combinations. (2000) — 685 citations
- On the Frustration to Predict Binding Affinities from Protein-Ligand Structures with Deep Neural Networks. (2022) — 156 citations
- Optimizing Fragment and Scaffold Docking by Use of Molecular Interaction Fingerprints (2007) — 396 citations
- Comparative evaluation of eight docking tools for docking and virtual screening accuracy (2004) — 556 citations