David B. Ascher
Molecular Biology · 2013–2022
A researcher in the Science corpus: 10 papers; trusts 34 researchers and is trusted by 14 researchers here, as inferred from the citation graph.
Subfields
- Molecular Biology — 123 citations into it; #2,790 of 17,773 by trust here, #5,968 by citations
- Materials Chemistry — 65 citations into it; #2,868 of 11,513 by trust here, #6,743 by citations
- Computational Biology & Bioinformatics — 37 citations into it
- Computational Theory and Mathematics — 35 citations into it; #4,665 of 12,182 by trust here, #1,936 by citations
- Spectroscopy — 22 citations into it
- Genetics — 8 citations into it
Whom David B. Ascher trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Douglas E. V. Pires
- Tom L. Blundell
- Emidio Capriotti
- Yves Dehouck
- Andrej Sali
- Carlos H. M. Rodrigues
- Pauline Crystal Ng
- Shuichi Kawashima
- M. Michael Gromiha
- Jianlin Cheng
Who trusts David B. Ascher overall
- Carlos H. M. Rodrigues
- Douglas E. V. Pires
- Kevin Kaichuang Yang
- Qisheng Pan
- Arun Prasad Pandurangan
- Zachary Wu
- Yoochan Myung
- Thanh-Binh Nguyen
- Bian Li
Papers from David B. Ascher's perspective
Ordered by how strongly the researchers David B. Ascher trusts endorse each paper. Same corpus, a different order for every researcher.
- ProTherm, version 4.0: thermodynamic database for proteins and mutants
- TM-align: a protein structure alignment algorithm based on the TM-score
- The Protein Data Bank.
- SCOP: a structural classification of proteins database for the investigation of sequences and structures.
- The Protein Data Bank
- Highly accurate protein structure prediction with AlphaFold
- Open Babel: An open chemical toolbox
- ProTherm and ProNIT: thermodynamic databases for proteins and protein–nucleic acid interactions (Nucleic Acids Res.)
- Improved protein structure prediction using potentials from deep learning
- The worldwide Protein Data Bank (wwPDB): ensuring a single, uniform archive of PDB data
Their papers
- mCSM: predicting the effects of mutations in proteins using graph-based signatures (2013) — 1,016 citations
- DUET: a server for predicting effects of mutations on protein stability using an integrated computational approach (2014) — 867 citations
- DynaMut: predicting the impact of mutations on protein conformation, flexibility and stability (2018) — 926 citations
- A structural biology community assessment of AlphaFold2 applications (2021) — 578 citations
- pkCSM: Predicting Small-Molecule Pharmacokinetic and Toxicity Properties Using Graph-Based Signatures (2015) — 4,911 citations
- Arpeggio: A Web Server for Calculating and Visualising Interatomic Interactions in Protein Structures (2017) — 448 citations
- SDM: a server for predicting effects of mutations on protein stability (2017) — 459 citations
- DynaMut2: Assessing changes in stability and flexibility upon single and multiple point missense mutations (2020) — 556 citations
- Systematic evaluation of computational tools to predict the effects of mutations on protein stability in the absence of experimental structures (2022) — 22 citations
- mCSM-PPI2: predicting the effects of mutations on protein–protein interactions (2019) — 309 citations