Stefan Seemayer

Molecular Biology · 2013–2018

A researcher in the Science corpus: 4 papers; trusts 32 researchers and is trusted by 36 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 107 citations into it; #1,079 of 17,773 by trust here, #3,681 by citations
• Computational Biology & Bioinformatics — 50 citations into it; #124 of 660 by trust here, #229 by citations
• Materials Chemistry — 20 citations into it
• Genetics — 17 citations into it
• Spectroscopy — 13 citations into it
• Probabilistic & Bayesian Methods — 8 citations into it

Whom Stefan Seemayer trusts overall

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

1. David T. Jones
2. Hetunandan Kamisetty
3. Debora Marks
4. Thomas A. Hopf
5. Sergey Ovchinnikov
6. Timothy Nugent
7. Geoffrey E. Hinton
8. Christopher Sander
9. Lucy J. Colwell
10. Martin Weigt

Who trusts Stefan Seemayer overall

1. Sheng Wang
2. Badri Adhikari
3. Daniel W. A. Buchan
4. Jinbo Xu
5. David T. Jones
6. Roshan Rao
7. Shaun M. Kandathil
8. Joe G. Greener
9. Robin Pearce
10. Alex Hawkins-Hooker

Papers from Stefan Seemayer's perspective

Ordered by how strongly the researchers Stefan Seemayer 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. HHblits: lightning-fast iterative protein sequence searching by HMM-HMM alignment
3. Direct-coupling analysis of residue coevolution captures native contacts across many protein families
4. Attention is All you Need (Neural Information Processing Systems)
5. Accurate de novo structure prediction of large transmembrane protein domains using fragment-assembly and correlated mutation analysis
6. 3D structures of membrane proteins from genomic sequencing
7. Correlated mutations and residue contacts in proteins
8. Long Short-Term Memory
9. The Pfam protein families database
10. Protein structure prediction from sequence variation

Their papers

• CCMpred—fast and precise prediction of protein residue–residue contacts from correlated mutations (2014) — 382 citations
• A large-scale evaluation of computational protein function prediction (2013) — 1,002 citations
• A structural model of the active ribosome-bound membrane protein insertase YidC (2014) — 87 citations
• Synthetic protein alignments by CCMgen quantify noise in residue-residue contact prediction (2018) — 22 citations