Andrea Pagnani

Molecular Biology · 2011–2021

A researcher in the Science corpus: 7 papers; trusts 36 researchers and is trusted by 44 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 223 citations into it; #761 of 17,773 by trust here, #1,171 by citations
• Computational Biology & Bioinformatics — 106 citations into it; #97 of 660 by trust here, #92 by citations
• Materials Chemistry — 71 citations into it
• Genetics — 58 citations into it; #5,744 of 6,854 by trust here, #3,998 by citations
• Probabilistic & Bayesian Methods — 15 citations into it
• Statistical and Nonlinear Physics — 12 citations into it
• Computational Theory and Mathematics — 10 citations into it
• Statistics and Probability — 8 citations into it

Whom Andrea Pagnani trusts overall

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

1. Martin Weigt
2. Sean R. Eddy
3. David John Cameron MacKay
4. John Moult
5. Yang Zhang
6. S. Parasuraman
7. Robert D. Finn
8. Lukas Burger
9. Joe G. Greener
10. E. Neher

Who trusts Andrea Pagnani overall

1. Anne-Florence Bitbol
2. Sergey Ovchinnikov
3. Thomas A. Hopf
4. Mirco Michel
5. Robin Pearce
6. David T. Jones
7. Debora Marks
8. Sheng Wang
9. Faruck Morcos
10. Marcin J. Skwark

Papers from Andrea Pagnani's perspective

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

1. Identification of direct residue contacts in protein–protein interaction by message passing
2. Protein 3D Structure Computed from Evolutionary Sequence Variation
3. Information Theory, Inference, and Learning Algorithms
4. Protein data bank
5. Improved contact prediction in proteins: using pseudolikelihoods to infer Potts models.
6. Emerging methods in protein co-evolution
7. A Learning Algorithm for Boltzmann Machines
8. Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model
9. Protein homology detection by HMM?CHMM comparison
10. Separation of phylogenetic and functional associations in biological sequences by using the parametric bootstrap.

Their papers

• Direct-coupling analysis of residue coevolution captures native contacts across many protein families (2011) — 1,436 citations
• Protein 3D Structure Computed from Evolutionary Sequence Variation (2011) — 1,167 citations
• Fast and Accurate Multivariate Gaussian Modeling of Protein Families: Predicting Residue Contacts and Protein-Interaction Partners (2014) — 137 citations
• Efficient generative modeling of protein sequences using simple autoregressive models (2021) — 95 citations
• Simultaneous identification of specifically interacting paralogs and interprotein contacts by direct coupling analysis (2016) — 117 citations
• Maximum-Entropy Models of Sequenced Immune Repertoires Predict Antigen-Antibody Affinity (2016) — 33 citations
• 3D Protein Structure Predicted from Sequence (2011) — 6 citations