Magnus Ekeberg
Molecular Biology · 2012–2017
A researcher in the Science corpus: 4 papers; trusts 35 researchers and is trusted by 34 researchers here, as inferred from the citation graph.
Subfields
- Molecular Biology — 72 citations into it; #1,073 of 17,773 by trust here, #4,050 by citations
- Computational Biology & Bioinformatics — 59 citations into it; #192 of 660 by trust here, #305 by citations
- Materials Chemistry — 15 citations into it
- Genetics — 10 citations into it
- Spectroscopy — 8 citations into it
- Statistical and Nonlinear Physics — 5 citations into it
Whom Magnus Ekeberg trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- S. Parasuraman
- Olivier Rivoire
- Aapo Hyvärinen
- Zhiyong Wang
- Debora Marks
- Hetunandan Kamisetty
- Thomas A. Hopf
- Martin Weigt
- Vitor Sessak
- David T. Jones
Who trusts Magnus Ekeberg overall
- E. van Nimwegen
- Duccio Malinverni
- Yang Li
- Sergey Ovchinnikov
- Santrupti Nerli
- Robin Pearce
- Gaëtan Hadjeres
- Thomas A. Hopf
- Simona Cocco
- Hetunandan Kamisetty
Papers from Magnus Ekeberg's perspective
Ordered by how strongly the researchers Magnus Ekeberg 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
- Scoring function for automated assessment of protein structure template quality
- Accurate de novo structure prediction of large transmembrane protein domains using fragment-assembly and correlated mutation analysis
- Protein data bank
- Assessing the utility of coevolution-based residue–residue contact predictions in a sequence- and structure-rich era
- Correlated mutations and residue contacts in proteins
- Improved contact prediction in proteins: using pseudolikelihoods to infer Potts models.
- Protein 3D Structure Computed from Evolutionary Sequence Variation
- Independent Component Analysis
Their papers
- Improved contact prediction in proteins: using pseudolikelihoods to infer Potts models. (2012) — 642 citations
- Fast pseudolikelihood maximization for direct-coupling analysis of protein structure from many homologous amino-acid sequences (2014) — 177 citations
- Predicting accurate contacts in thousands of Pfam domain families using PconsC3 (2017) — 42 citations
- Accurate contact predictions for thousands of protein families using PconsC3 (2016) — 4 citations