Alex Ford
Molecular Biology · 2016–2020
A researcher in the Science corpus: 6 papers; trusts 4 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Molecular Biology — 358 citations into it; #11,348 of 17,773 by trust here, #4,273 by citations
- Materials Chemistry — 174 citations into it
- Physical and Theoretical Chemistry — 6 citations into it
Whom Alex Ford trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Nicholas B Rego
- L. Nivón
- Patrick Conway
- David Ryan Koes
- David Baker
- Michael D. Tyka
- S. Bjelic
- Frank DiMaio
Who trusts Alex Ford overall
Papers from Alex Ford's perspective
Ordered by how strongly the researchers Alex Ford trusts endorse each paper. Same corpus, a different order for every researcher.
- Efficient Sampling of Protein Conformational Space Using Fast Loop Building and Batch Minimization on Highly Parallel Computers
- Modeling T cell receptor recognition of CD1-lipid and MR1-metabolite complexes
- T-Cell Transfer Therapy Targeting Mutant KRAS in Cancer
- Systematic Comparison of Amber and Rosetta Energy Functions for Protein Structure Evaluation.
- Repurposing Citizen Science Games as Software Tools for Professional Scientists
- A flexible docking approach for prediction of T cell receptor–peptide–MHC complexes
- Can Self-Inhibitory Peptides be Derived from the Interfaces of Globular Protein-Protein Interactions?
- Systematic Analysis of Helical Protein Interfaces Reveals Targets for Synthetic Inhibitors
- RosettaHoles: Rapid assessment of protein core packing for structure prediction, refinement, design, and validation
- Comprehensive Analysis of Loops at Protein-Protein Interfaces for Macrocycle Design
Their papers
- De novo protein design by citizen scientists (2019) — 131 citations
- Global analysis of protein folding using massively parallel design, synthesis, and testing (2017) — 497 citations
- Macromolecular modeling and design in Rosetta: recent methods and frameworks (2020) — 783 citations
- De novo design of protein homo-oligomers with modular hydrogen-bond network–mediated specificity (2016) — 295 citations
- De novo design of covalently constrained mesosize protein scaffolds with unique tertiary structures (2017) — 48 citations
- Integration of the Rosetta suite with the python software stack via reproducible packaging and core programming interfaces for distributed simulation (2019) — 18 citations