Matteo Figliuzzi
Molecular Biology · 2015–2020
A researcher in the Science corpus: 4 papers; trusts 18 researchers and is trusted by 9 researchers here, as inferred from the citation graph.
Subfields
- Molecular Biology — 138 citations into it; #6,266 of 17,773 by trust here, #7,496 by citations
- Computational Biology & Bioinformatics — 71 citations into it
- Genetics — 54 citations into it
- Probabilistic & Bayesian Methods — 12 citations into it
Whom Matteo Figliuzzi trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Thomas A. Hopf
- Debora Marks
- Martin Weigt
- Sergey Ovchinnikov
- David T. Jones
- Faruck Morcos
- Christopher Sander
- Sean R. Eddy
- Hetunandan Kamisetty
- Alexander Schug
Who trusts Matteo Figliuzzi overall
- Alex Hawkins-Hooker
- Joshua Meier
- J. Trinquier
- Jakub Otwinowski
- F. Depardieu
- Alexander Rives
- Guido Uguzzoni
- Jérôme Tubiana
- Roshan Rao
- Sebastien Baur
Papers from Matteo Figliuzzi's perspective
Ordered by how strongly the researchers Matteo Figliuzzi trusts endorse each paper. Same corpus, a different order for every researcher.
- Identification of direct residue contacts in protein–protein interaction by message passing
- Direct-coupling analysis of residue coevolution captures native contacts across many protein families
- The Pfam protein families database
- Protein 3D Structure Computed from Evolutionary Sequence Variation
- Protein structure prediction from sequence variation
- Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids
- Profile hidden Markov models
- PSICOV: precise structural contact prediction using sparse inverse covariance estimation on large multiple sequence alignments
- Emerging methods in protein co-evolution
- Attention is All you Need (Neural Information Processing Systems)
Their papers
- Coevolutionary Landscape Inference and the Context-Dependence of Mutations in Beta-Lactamase TEM-1 (2015) — 252 citations
- How Pairwise Coevolutionary Models Capture the Collective Residue Variability in Proteins? (2018) — 117 citations
- An evolution-based model for designing chorismate mutase enzymes (2020) — 297 citations
- Inverse statistical physics of protein sequences: a key issues review (2017) — 242 citations