Mor Nitzan
Molecular Biology · 2019–2021
A researcher in the Science corpus: 2 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Molecular Biology — 35 citations into it
- Computational Biology & Bioinformatics — 12 citations into it
Whom Mor Nitzan trusts
Their strongest outbound trust, strongest first, inferred from their citations.
- Hetunandan Kamisetty (in Molecular Biology)
Papers from Mor Nitzan's perspective
Ordered by how strongly the researchers Mor Nitzan trusts endorse each paper. Same corpus, a different order for every researcher.
- Identification of direct residue contacts in protein–protein interaction by message passing
- Learning generative models for protein fold families
- PSICOV: precise structural contact prediction using sparse inverse covariance estimation on large multiple sequence alignments
- Direct-coupling analysis of residue coevolution captures native contacts across many protein families
- Correlated mutations in models of protein sequences: phylogenetic and structural effects
- Improved contact prediction in proteins: using pseudolikelihoods to infer Potts models.
- Assessing the utility of coevolution-based residue–residue contact predictions in a sequence- and structure-rich era
- Fast and Accurate Multivariate Gaussian Modeling of Protein Families: Predicting Residue Contacts and Protein-Interaction Partners
- Statistical Analysis of Non-Lattice Data
- Mutual information without the influence of phylogeny or entropy dramatically improves residue contact prediction
Their papers
- Unified framework for modeling multivariate distributions in biological sequences (2019) — 11 citations
- Deep learning and alignment of spatially-resolved single cell transcriptomes with Tangram (2021) — 721 citations