Enrique Marcos
Molecular Biology · 2017–2022
A researcher in the Science corpus: 8 papers; trusts 41 researchers and is trusted by 1 researcher here, as inferred from the citation graph.
Subfields
- Molecular Biology — 430 citations into it; #15,393 of 17,773 by trust here, #5,452 by citations
- Materials Chemistry — 216 citations into it; #10,312 of 11,513 by trust here, #6,365 by citations
- Computational Biology & Bioinformatics — 82 citations into it
- Radiology, Nuclear Medicine and Imaging — 64 citations into it; #3,055 of 3,265 by trust here, #2,914 by citations
- Computational Theory and Mathematics — 52 citations into it
- Spectroscopy — 52 citations into it
- Computational Chemistry & Drug Discovery — 41 citations into it
- AI for Physical Sciences — 11 citations into it
Whom Enrique Marcos trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- David Baker
- Andrew Leaver-Fay
- Michael D. Tyka
- Philip Bradley
- Adrian A. Canutescu
- Amelie Stein
- Lindsey Doyle
- G. Sheldrick
- Carol A. Rohl
- Daniel J. Mandell
Who trusts Enrique Marcos overall
- Xingjie Pan
- I. Korendovych
- Daniel Peñas-Utrilla
- William F. DeGrado
- Tanja Kortemme
- Mostafa Karimi
- Namrata Anand
- Julia Koehler Leman
- Thomas W. Linsky
- Daniel‐Adriano Silva
Papers from Enrique Marcos's perspective
Ordered by how strongly the researchers Enrique Marcos trusts endorse each paper. Same corpus, a different order for every researcher.
- Alternate states of proteins revealed by detailed energy landscape mapping
- 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
- Structure-based prediction of the peptide sequence space recognized by natural and synthetic PDZ domains.
- Predicting the Tolerated Sequences for Proteins and Protein Interfaces Using RosettaBackrub Flexible Backbone Design
Their papers
- De novo design of a non-local β-sheet protein with high stability and accuracy (2018) — 107 citations
- Principles for designing proteins with cavities formed by curved β-sheets (2017) — 130 citations
- Macromolecular modeling and design in Rosetta: recent methods and frameworks (2020) — 783 citations
- De novo design of a fluorescence-activating β-barrel (2018) — 312 citations
- Essentials of de novo protein design: Methods and applications (2018) — 54 citations
- Identifying well-folded de novo proteins in the new era of accurate structure prediction (2022) — 8 citations
- De novo design of potent and selective mimics of IL-2 and IL-15 (2019) — 474 citations
- De novo design of a non-local beta-sheet protein with high stability and accuracy (2018)