Yves Dehouck

Molecular Biology · 2007–2013

A researcher in the Science corpus: 5 papers; trusts 12 researchers and is trusted by 13 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 51 citations into it; #4,391 of 17,773 by trust here, #9,367 by citations
• Materials Chemistry — 22 citations into it
• Computational Biology & Bioinformatics — 8 citations into it
• Computational Theory and Mathematics — 6 citations into it; #9,305 of 12,182 by trust here, #4,696 by citations
• Spectroscopy — 6 citations into it

Whom Yves Dehouck trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. S. Parasuraman
2. Dimitri Gilis
3. Hongyi Zhou
4. Yanay Ofran
5. Marianne Rooman
6. Vijaya Parthiban
7. Kurt S. Thorn
8. Jianlin Cheng
9. M. Michael Gromiha
10. Craig T. Porter

Who trusts Yves Dehouck overall

1. Douglas E. V. Pires
2. Lijun Quan
3. Bian Li
4. David B. Ascher
5. Yang Zhang
6. Jeffrey R. Brender
7. Jean Marc Kwasigroch
8. Abhishek Niroula
9. Carlos H. M. Rodrigues
10. Qiang Lv

Papers from Yves Dehouck's perspective

Ordered by how strongly the researchers Yves Dehouck trusts endorse each paper. Same corpus, a different order for every researcher.

1. The Protein Data Bank.
2. Predicting changes in the stability of proteins and protein complexes: a study of more than 1000 mutations.
3. Distance‐scaled, finite ideal‐gas reference state improves structure‐derived potentials of mean force for structure selection and stability prediction
4. Principles of protein-protein interactions (European Conference on Computational Biology)
5. Dictionary of protein secondary structure: Pattern recognition of hydrogen‐bonded and geometrical features
6. Prediction of protein stability changes for single‐site mutations using support vector machines
7. Protein data bank
8. Predicting protein stability changes upon mutation using database-derived potentials: solvent accessibility determines the importance of local versus non-local interactions along the sequence.
9. Selection of representative protein data sets
10. Optimization of affinity, specificity and function of designed influenza inhibitors using deep sequencing

Their papers

• Fast and accurate predictions of protein stability changes upon mutations using statistical potentials and neural networks: PoPMuSiC-2.0 (2009) — 399 citations
• PoPMuSiC 2.1: a web server for the estimation of protein stability changes upon mutation and sequence optimality (2011) — 527 citations
• Enhancing the stability and solubility of TEV protease using in silico design (2007) — 168 citations
• BeAtMuSiC: prediction of changes in protein–protein binding affinity on mutations (2013) — 327 citations
• Community‐wide evaluation of methods for predicting the effect of mutations on protein–protein interactions (2013) — 102 citations