Kelly P. Brock
Molecular Biology · 2018–2021
A researcher in the Science corpus: 7 papers; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Molecular Biology — 190 citations into it
- Computational Biology & Bioinformatics — 90 citations into it
Whom Kelly P. Brock trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Papers from Kelly P. Brock's perspective
Ordered by how strongly the researchers Kelly P. Brock trusts endorse each paper. Same corpus, a different order for every researcher.
- Protein 3D Structure Computed from Evolutionary Sequence Variation
- Highly accurate protein structure prediction with AlphaFold
- Deep mutational scanning: a new style of protein science
- Semi-supervised Learning with Deep Generative Models
- Deep Learning
- Highly accurate protein structure prediction for the human proteome
- AUTO-ENCODING VARIATIONAL BAYES
- PDBe: improved findability of macromolecular structure data in the PDB
- Faculty Opinions recommendation of Accurate prediction of protein structures and interactions using a three-track neural network.
- Using Sequence Alignments to Predict Protein Structure and Stability With High Accuracy
Their papers
- The EVcouplings Python framework for coevolutionary sequence analysis (2018) — 276 citations
- Large-scale discovery of protein interactions at residue resolution using co-evolution calculated from genomic sequences (2021) — 103 citations
- Inferring protein 3D structure from deep mutation scans (2019) — 143 citations
- Disease variant prediction with deep generative models of evolutionary data (2021) — 734 citations
- PDBe-KB: collaboratively defining the biological context of structural data (2021) — 68 citations
- Large-scale clinical interpretation of genetic variants using evolutionary data and deep learning (2020) — 21 citations
- Proteome-scale discovery of protein interactions with residue-level resolution using sequence coevolution (2019) — 6 citations