Vikram Khipple Mulligan
Molecular Biology · 2013–2020
A researcher in the Science corpus: 14 papers; trusts 6 researchers and is trusted by 9 researchers here, as inferred from the citation graph.
Subfields
- Molecular Biology — 482 citations into it; #4,049 of 17,773 by trust here, #1,631 by citations
- Materials Chemistry — 245 citations into it; #4,327 of 11,513 by trust here, #2,967 by citations
- Computational Biology & Bioinformatics — 75 citations into it
- Spectroscopy — 53 citations into it
Whom Vikram Khipple Mulligan trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- David Baker
- Andrew Leaver-Fay
- Sarel Jacob Fleishman
- Brian Kuhlman
- S. Gonen
- Frank DiMaio
- N. Koga
- S. Parasuraman
- Daniel J. Mandell
- Scott E. Boyken
Who trusts Vikram Khipple Mulligan overall
Papers from Vikram Khipple Mulligan's perspective
Ordered by how strongly the researchers Vikram Khipple Mulligan trusts endorse each paper. Same corpus, a different order for every researcher.
- Native protein sequences are close to optimal for their structures.
- RosettaHoles: Rapid assessment of protein core packing for structure prediction, refinement, design, and validation
- Alternate states of proteins revealed by detailed energy landscape mapping
- Design of a Novel Globular Protein Fold with Atomic-Level Accuracy
- 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?
Their papers
- The Rosetta all-atom energy function for macromolecular modeling and design (2017) — 1,486 citations
- Simultaneous optimization of biomolecular energy function on features from small molecules and macromolecules (2016) — 510 citations
- Global analysis of protein folding using massively parallel design, synthesis, and testing (2017) — 497 citations
- Comprehensive computational design of ordered peptide macrocycles (2017) — 183 citations
- Accurate de novo design of hyperstable constrained peptides (2016) — 389 citations
- Macromolecular modeling and design in Rosetta: recent methods and frameworks (2020) — 783 citations
- Programmable design of orthogonal protein heterodimers (2018) — 167 citations
- De novo design of covalently constrained mesosize protein scaffolds with unique tertiary structures (2017) — 48 citations
- Accurate computational design of multipass transmembrane proteins (2018) — 159 citations
- De Novo Design of Bioactive Protein Switches (2019) — 242 citations
- Designing Peptides on a Quantum Computer (2019) — 58 citations
- Better together: Elements of successful scientific software development in a distributed collaborative community (2020) — 37 citations
- A computational method for the design of nested proteins by loop‐directed domain insertion (2018) — 3 citations
- Computational Design of an Unnatural Amino Acid Dependent Metalloprotein with Atomic Level Accuracy (2013) — 104 citations