Bingding Huang

Molecular Biology · 2006–2009

A researcher in the Science corpus: 2 papers; trusts 11 researchers and is trusted by 20 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 13 citations into it; #2,149 of 17,773 by trust here, #10,695 by citations
• Computational Theory and Mathematics — 6 citations into it; #2,101 of 12,182 by trust here, #3,796 by citations
• Materials Chemistry — 6 citations into it
• Cell Biology — 5 citations into it

Whom Bingding Huang trusts overall

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

1. Martin Weisel
2. Alasdair T. R. Laurie
3. James R. Bradford
4. Aharon Armon
5. Tal Pupko
6. Ewgenij Proschak
7. Richard M. Jackson
8. David R. Westhead
9. Dan-Ovidiu Graur
10. Gisbert Schneider

Who trusts Bingding Huang overall

1. Gabriele Macari
2. David K. Johnson
3. John Karanicolas
4. Daniel B. Roche
5. Karen R. Khar
6. Zhuguo Li
7. Jian Yu
8. Daniele Toti
9. John A. Capra
10. Dima Kozakov

Papers from Bingding Huang's perspective

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

1. The PyMOL Molecular Graphics System
2. ConSurf: an algorithmic tool for the identification of functional regions in proteins by surface mapping of phylogenetic information. (Journal of Molecular Biology)
3. CASTp: Computed Atlas of Surface Topography of proteins (Nucleic Acids Res.)
4. Principles of docking: An overview of search algorithms and a guide to scoring functions
5. A new test set for validating predictions of protein–ligand interaction (Proteins: Structure, Function, and Bioinformatics)
6. Rate4Site: an algorithmic tool for the identification of functional regions in proteins by surface mapping of evolutionary determinants within their homologues (Intelligent Systems in Molecular Biology)
7. Improved prediction of protein-protein binding sites using a support vector machines approach. (Bioinformatics)
8. PocketPicker: analysis of ligand binding-sites with shape descriptors (Chemistry Central Journal)
9. The Protein Data Bank.
10. Fast prediction and visualization of protein binding pockets with PASS

Their papers

• LIGSITEcsc: predicting ligand binding sites using the Connolly surface and degree of conservation (2006) — 451 citations
• MetaPocket: A Meta Approach to Improve Protein Ligand Binding Site Prediction (2009) — 381 citations