E. van Nimwegen
Molecular Biology · 2003–2016
A researcher in the Science corpus: 12 papers; trusts 57 researchers and is trusted by 55 researchers here, as inferred from the citation graph.
Subfields
- Molecular Biology — 214 citations into it; #601 of 17,773 by trust here, #1,482 by citations
- Genetics — 32 citations into it; #2,943 of 6,854 by trust here, #4,897 by citations
- Computational Biology & Bioinformatics — 29 citations into it
- Materials Chemistry — 14 citations into it
- Probabilistic & Bayesian Methods — 11 citations into it
- Artificial Intelligence — 7 citations into it
- Ecology — 5 citations into it
Whom E. van Nimwegen trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Magnus Ekeberg
- Lukas Burger
- Eugene V. Koonin
- Martin Weigt
- Robert D. Finn
- Faruck Morcos
- Sean R. Eddy
- Anthony Fodor
- Tuomo Hartonen
- Erik Aurell
Who trusts E. van Nimwegen overall
- H. C. Nguyen
- Riccardo Zecchina
- Eugene V. Koonin
- Debora Marks
- Martin Weigt
- Marcin J. Skwark
- Anne-Florence Bitbol
- John S. Mattick
- Larry J Croft
- Lukas Burger
Papers from E. van Nimwegen's perspective
Ordered by how strongly the researchers E. van Nimwegen trusts endorse each paper. Same corpus, a different order for every researcher.
- The Pfam protein families database
- 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
- Separation of phylogenetic and functional associations in biological sequences by using the parametric bootstrap.
- Mutual information without the influence of phylogeny or entropy dramatically improves residue contact prediction
- CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice.
- Information Theory: 1948-1998 - Guest Editorial
- Improved contact prediction in proteins: using pseudolikelihoods to infer Potts models.
- Gapped BLAST and PSI-BLAST: a new generation of protein database search programs.
- Accurate prediction of protein–protein interactions from sequence alignments using a Bayesian method
Their papers
- Disentangling Direct from Indirect Co-Evolution of Residues in Protein Alignments (2010) — 214 citations
- The Transcriptional Landscape of the Mammalian Genome (2005) — 3,572 citations
- Accurate prediction of protein–protein interactions from sequence alignments using a Bayesian method (2008) — 190 citations
- Automated Reconstruction of Whole-Genome Phylogenies from Short-Sequence Reads (2014) — 441 citations
- An atlas of combinatorial transcriptional regulation in mouse and man (2010) — 688 citations
- PhyloGibbs: A Gibbs Sampling Motif Finder That Incorporates Phylogeny (2005) — 309 citations
- A promoter-level mammalian expression atlas (2014) — 1,941 citations
- Scaling Laws in the Functional Content of Genomes (2003) — 361 citations
- Inferring Contacting Residues within and between Proteins: What Do the Probabilities Mean? (2016) — 20 citations
- ISMARA: automated modeling of genomic signals as a democracy of regulatory motifs (2014) — 300 citations
- The SIB Swiss Institute of Bioinformatics’ resources: focus on curated databases (2015) — 60 citations
- An Atlas of Combinatorial Transcriptional Regulation in Mouse and Man (vol 140, pg 744, 2010) (2010) — 107 citations