H. Szurmant
Molecular Biology · 2007–2017
A researcher in the Science corpus: 9 papers; trusts 53 researchers and is trusted by 48 researchers here, as inferred from the citation graph.
Subfields
- Molecular Biology — 136 citations into it; #554 of 17,773 by trust here, #2,235 by citations
- Computational Biology & Bioinformatics — 56 citations into it; #117 of 660 by trust here, #212 by citations
- Genetics — 35 citations into it; #182 of 6,854 by trust here, #462 by citations
- Materials Chemistry — 24 citations into it; #6,371 of 11,513 by trust here, #8,250 by citations
- Spectroscopy — 18 citations into it
- Probabilistic & Bayesian Methods — 10 citations into it
- Computational Theory and Mathematics — 7 citations into it
- Artificial Intelligence — 6 citations into it
Whom H. Szurmant trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Matteo Pellegrini
- David T. Jones
- Hetunandan Kamisetty
- Sean R. Eddy
- Martin Weigt
- J. Hoch
- Kim D. Pruitt
- Robert A. H. White
- Sergey Ovchinnikov
- Lukas Burger
Who trusts H. Szurmant overall
- Anne-Florence Bitbol
- Ryan R. Cheng
- Martin Weigt
- Alexander Schug
- Faruck Morcos
- Andrea Procaccini
- Matteo Figliuzzi
- Bryan Lunt
- Robin Pearce
- A. E. Dago
Papers from H. Szurmant's perspective
Ordered by how strongly the researchers H. Szurmant trusts endorse each paper. Same corpus, a different order for every researcher.
- Identification of direct residue contacts in protein–protein interaction by message passing
- The Pfam protein families database
- Direct-coupling analysis of residue coevolution captures native contacts across many protein families
- Protein 3D Structure Computed from Evolutionary Sequence Variation
- Gapped BLAST and PSI-BLAST: a new generation of protein database search programs.
- Accurate de novo structure prediction of large transmembrane protein domains using fragment-assembly and correlated mutation analysis
- Profile hidden Markov models
- 3D structures of membrane proteins from genomic sequencing
- Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids
- Assessing the utility of coevolution-based residue–residue contact predictions in a sequence- and structure-rich era
Their papers
- Identification of direct residue contacts in protein–protein interaction by message passing (2009) — 1,014 citations
- High-resolution protein complexes from integrating genomic information with molecular simulation (2009) — 149 citations
- Structural basis of histidine kinase autophosphorylation deduced by integrating genomics, molecular dynamics, and mutagenesis (2012) — 143 citations
- Computational modeling of phosphotransfer complexes in two-component signaling. (2010) — 19 citations
- Large-scale identification of coevolution signals across homo-oligomeric protein interfaces by direct coupling analysis (2017) — 97 citations
- Features of protein-protein interactions in two-component signaling deduced from genomic libraries. (2007) — 54 citations
- Inference of direct residue contacts in two-component signaling. (2010) — 45 citations
- Dissecting the Specificity of Protein-Protein Interaction in Bacterial Two-Component Signaling: Orphans and Crosstalks (2011) — 89 citations
- Inter-residue, inter-protein and inter-family coevolution: bridging the scales (2017) — 73 citations