Jeff Flatten
2017–2019
A researcher in the Science corpus: 3 papers; trusts 0 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Whom Jeff Flatten trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Papers from Jeff Flatten's perspective
Ordered by how strongly the researchers Jeff Flatten trusts endorse each paper. Same corpus, a different order for every researcher.
- The Rosetta all-atom energy function for macromolecular modeling and design
- Predicting protein structures with a multiplayer online game
- ROSETTALIGAND: Protein–small molecule docking with full side‐chain flexibility
- The PyMOL Molecular Graphics System
- Foldit Standalone: a video game-derived protein structure manipulation interface using Rosetta
- 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
Their papers
- De novo protein design by citizen scientists (2019) — 131 citations
- Foldit Standalone: a video game-derived protein structure manipulation interface using Rosetta (2017) — 101 citations
- Creating Custom Foldit Puzzles for Teaching Biochemistry (2019) — 29 citations