Kevin J. Karplus

Molecular Biology · 1997–2011

A researcher in the Science corpus: 9 papers; trusts 27 researchers and is trusted by 87 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 36 citations into it; #659 of 17,773 by trust here, #2,259 by citations
• Computational Biology & Bioinformatics — 32 citations into it; #68 of 660 by trust here, #142 by citations
• Materials Chemistry — 10 citations into it; #586 of 11,513 by trust here, #7,310 by citations
• Spectroscopy — 8 citations into it
• Algorithms & Complexity — 7 citations into it

Whom Kevin J. Karplus trusts overall

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

1. Anders Krogh
2. Stephen F. Altschul
3. Guoli Wang
4. Roger A. Sayle
5. Christopher Sander
6. William R. Pearson
7. Liisa Holm
8. Carol A. Rohl
9. Steven Henikoff
10. D. van der Spoel

Who trusts Kevin J. Karplus overall

1. Sean R. Eddy
2. Yang Zhang
3. Ben M. Webb
4. Julian Gough
5. Bohdan Monastyrskyy
6. Andrej Sali
7. Björn Wallner
8. Ke Chen
9. Marc A. Martí-Renom
10. Eric D. Scheeff

Papers from Kevin J. Karplus's perspective

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

1. Hidden Markov models in computational biology. Applications to protein modeling.
2. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs.
3. Protein structure comparison by alignment of distance matrices.
4. Hidden Markov models for detecting remote protein homologies
5. Assessing sequence comparison methods with reliable structurally identified distant evolutionary relationships.
6. Statistical Decision Theory and Bayesian Analysis, Second Edition
7. The Protein Data Bank.
8. The HSSP data base of protein structure-sequence alignments
9. PHD: predicting one-dimensional protein structure by profile-based neural networks.
10. SCOP: a structural classification of proteins database for the investigation of sequences and structures.

Their papers

• Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega (2011) — 15,106 citations
• Contact prediction using mutual information and neural nets (2007) — 129 citations
• SAM-T08, HMM-based protein structure prediction (2009) — 140 citations
• Assignment of homology to genome sequences using a library of hidden Markov models that represent all proteins of known structure. (2001) — 1,256 citations
• Improving physical realism, stereochemistry and side-chain accuracy in homology modeling: four approaches that performed well in CASP8 (2009) — 543 citations
• Classifying G-protein coupled receptors with support vector machines (2002) — 297 citations
• Sequence comparisons using multiple sequences detect three times as many remote homologues as pairwise methods. (1998)
• Hidden Markov models for detecting remote protein homologies (1998)
• Predicting protein structure using hidden Markov models (1997)