Pierre Bruneau

Computational Theory and Mathematics · 2006

A researcher in the Science corpus: 2 papers; trusts 2 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Computational Theory and Mathematics — 11 citations into it; #5,884 of 12,182 by trust here, #4,531 by citations
• Materials Chemistry — 5 citations into it; #4,938 of 11,513 by trust here, #10,540 by citations
• Spectroscopy — 5 citations into it; #524 of 1,674 by trust here, #1,007 by citations

Whom Pierre Bruneau trusts overall

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

1. Igor V. Tetko
2. Christopher A. Lipinski
3. Roberto Todeschini
4. Andreas Bender

Who trusts Pierre Bruneau overall

1. Igor V. Tetko
2. Igor I. Baskin
3. Michael J. Waring
4. David A. Winkler
5. Timon Schroeter
6. Gennadiy Poda
7. Raimund Mannhold

Papers from Pierre Bruneau's perspective

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

1. The Importance of Being Earnest: Validation is the Absolute Essential for Successful Application and Interpretation of QSPR Models
2. Prediction of n-Octanol/Water Partition Coefficients from PHYSPROP Database Using Artificial Neural Networks and E-State Indices (Journal of chemical information and computer sciences)
3. Handbook of Molecular Descriptors
4. Molecular similarity: a key technique in molecular informatics. (Organic and biomolecular chemistry)
5. Current Status of Methods for Defining the Applicability Domain of (Quantitative) Structure-Activity Relationships (Alternatives to laboratory animals : ATLA)
6. Integrating virtual screening in lead discovery.
7. Application of Associative Neural Networks for Prediction of Lipophilicity in ALOGPS 2.1 Program (Journal of chemical information and computer sciences)
8. logD7.4 Modeling Using Bayesian Regularized Neural Networks. Assessment and Correction of the Errors of Prediction
9. Drug-like properties and the causes of poor solubility and poor permeability. (Journal of pharmacological and toxicological methods)
10. Methods for reliability and uncertainty assessment and for applicability evaluations of classification- and regression-based QSARs. (Environmental Health Perspectives)

Their papers

• Can we estimate the accuracy of ADME-Tox predictions? (2006) — 239 citations
• logD7.4 Modeling Using Bayesian Regularized Neural Networks. Assessment and Correction of the Errors of Prediction (2006) — 63 citations