James S. Fraser
Molecular Biology · 2012–2023
A researcher in the Science corpus: 17 papers; trusts 17 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Molecular Biology — 294 citations into it; #8,526 of 17,773 by trust here, #2,983 by citations
- Materials Chemistry — 124 citations into it; #5,383 of 11,513 by trust here, #6,473 by citations
- Computational Biology & Bioinformatics — 92 citations into it
- Computational Chemistry & Drug Discovery — 30 citations into it
- Computational Theory and Mathematics — 21 citations into it; #9,755 of 12,182 by trust here, #1,890 by citations
- Structural Biology — 20 citations into it; #196 of 224 by trust here, #81 by citations
- Surfaces, Coatings and Films — 12 citations into it
- Organic Chemistry — 7 citations into it
Whom James S. Fraser trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- R. Grosse-Kunstleve
- Colin A. Smith
- Pavel V. Afonine
- Tanja Kortemme
- G. Winter
- Michael M. Mysinger
- Paul D. Adams
- Tom Burnley
Who trusts James S. Fraser overall
Papers from James S. Fraser's perspective
Ordered by how strongly the researchers James S. Fraser trusts endorse each paper. Same corpus, a different order for every researcher.
- High resolution protein structure prediction and the crystallographic phase problem
- Alternate states of proteins revealed by detailed energy landscape mapping
- Use of knowledge-based restraints in phenix.refine to improve macromolecular refinement at low resolution
- Considerations for the refinement of low-resolution crystal structures.
- A simple physical model for binding energy hot spots in protein–protein complexes
- ISOLDE: a physically realistic environment for model building into low-resolution electron-density maps
- Joint X-ray and neutron refinement with phenix.refine.
- Computational design of proteins targeting the conserved stem region of influenza hemagglutinin
- HHblits: lightning-fast iterative protein sequence searching by HMM-HMM alignment
- Design of a Novel Globular Protein Fold with Atomic-Level Accuracy
Their papers
- From deep TLS validation to ensembles of atomic models built from elemental motions. Addenda and corrigendum (2016) — 6 citations
- Expanding the space of protein geometries by computational design of de novo fold families (2020) — 63 citations
- EMRinger: Side-chain-directed model and map validation for 3D Electron Cryomicroscopy (2015) — 699 citations
- Methods in Enzymology: “Flexible backbone sampling methods to model and design protein alternative conformations” (2013) — 43 citations
- A SARS-CoV-2 Protein Interaction Map Reveals Targets for Drug-Repurposing (2020) — 3,895 citations
- Control of protein signaling using a computationally designed GTPase/GEF orthogonal pair (2012) — 86 citations
- Computational design of a modular protein sense/response system (2019) — 124 citations
- Automated structure refinement of macromolecular assemblies from cryo-EM maps using Rosetta (2016) — 444 citations
- Deep neural language modeling enables functional protein generation across families (2021) — 55 citations
- Promoting transparency and reproducibility in enhanced molecular simulations (2019) — 1,046 citations
- Discovery and characterization of gut microbiota decarboxylases that can produce the neurotransmitter tryptamine (2014) — 609 citations
- CryoEM and AI reveal a structure of SARS-CoV-2 Nsp2, a multifunctional protein involved in key host processes. (2021) — 72 citations
- Large language models generate functional protein sequences across diverse families (2023) — 1,084 citations
- Comparative host-coronavirus protein interaction networks reveal pan-viral disease mechanisms. (2020) — 659 citations
- Bringing diffuse X-ray scattering into focus (2017) — 24 citations
- Meeting Review: Diffuse X-Ray Scattering to Model Protein Motions (2014)
- The incorporation of protein flexibility and conformational energy penalties in docking screens to improve ligand discovery (2014) — 139 citations