Barak Raveh

Molecular Biology · 2010–2020

A researcher in the Science corpus: 6 papers; trusts 15 researchers and is trusted by 11 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 316 citations into it; #4,189 of 17,773 by trust here, #5,405 by citations
• Materials Chemistry — 153 citations into it
• Computational Biology & Bioinformatics — 37 citations into it
• Spectroscopy — 35 citations into it; #638 of 1,674 by trust here, #618 by citations

Whom Barak Raveh trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Rhiju Das
2. David Baker
3. Brian Kuhlman
4. Daniel J. Mandell
5. Carol A. Rohl
6. Tony Pawson
7. Nir London
8. O. Schueler‐Furman
9. John A. Capra
10. S. Parasuraman

Who trusts Barak Raveh overall

1. Nir London
2. Isak Johansson-Åkhe
3. Andy Chi-Lung Lee
4. O. Schueler‐Furman
5. Tomer Tsaban
6. Sidhartha Chaudhury
7. Björn Wallner
8. J. Harris
9. Eyal Cohen
10. Brian D. Weitzner

Papers from Barak Raveh's perspective

Ordered by how strongly the researchers Barak Raveh trusts endorse each paper. Same corpus, a different order for every researcher.

1. Native protein sequences are close to optimal for their structures.
2. Protein data bank
3. Modeling T cell receptor recognition of CD1-lipid and MR1-metabolite complexes
4. T-Cell Transfer Therapy Targeting Mutant KRAS in Cancer
5. Systematic Comparison of Amber and Rosetta Energy Functions for Protein Structure Evaluation.
6. Repurposing Citizen Science Games as Software Tools for Professional Scientists
7. A flexible docking approach for prediction of T cell receptor–peptide–MHC complexes
8. Systematic Analysis of Helical Protein Interfaces Reveals Targets for Synthetic Inhibitors
9. The Protein Data Bank.
10. Predicting changes in the stability of proteins and protein complexes: a study of more than 1000 mutations.

Their papers

• Can Self-Inhibitory Peptides be Derived from the Interfaces of Globular Protein-Protein Interactions? (2010) — 167 citations
• Macromolecular modeling and design in Rosetta: recent methods and frameworks (2020) — 783 citations
• Sub‐angstrom modeling of complexes between flexible peptides and globular proteins (2010) — 415 citations
• Autophosphorylation Activates Dictyostelium Myosin II Heavy Chain Kinase A by Providing a Ligand for an Allosteric Binding Site in the α-Kinase Domain* (2010) — 25 citations
• Rosetta FlexPepDock web server—high resolution modeling of peptide–protein interactions (2011) — 396 citations
• Rosetta FlexPepDock ab-initio: Simultaneous Folding, Docking and Refinement of Peptides onto Their Receptors (2011) — 297 citations