Luciano A. Abriata

Molecular Biology · 2015–2020

A researcher in the Science corpus: 6 papers; trusts 30 researchers and is trusted by 11 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 114 citations into it; #8,921 of 17,773 by trust here, #7,911 by citations
• Computational Biology & Bioinformatics — 58 citations into it; #417 of 660 by trust here, #454 by citations
• Materials Chemistry — 49 citations into it; #5,482 of 11,513 by trust here, #6,608 by citations
• Genetics — 18 citations into it; #2,075 of 6,854 by trust here, #5,952 by citations
• Spectroscopy — 12 citations into it

Whom Luciano A. Abriata trusts overall

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

1. Andriy Kryshtafovych
2. Yang Zhang
3. Lisa N. Kinch
4. Bohdan Monastyrskyy
5. Sergey Ovchinnikov
6. Krzysztof Fidelis
7. John Moult
8. Jeffrey Skolnick
9. Jinrui Xu
10. Vladimir Potapov

Who trusts Luciano A. Abriata overall

1. Lisa N. Kinch
2. Sergey Ovchinnikov
3. Andriy Kryshtafovych
4. J. Haas
5. Emiliano Brini
6. Ahmed Elnaggar
7. Gyu Rie Lee
8. Giorgio Tamò
9. Wei Zheng
10. Michael Heinzinger

Papers from Luciano A. Abriata's perspective

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

1. Scoring function for automated assessment of protein structure template quality
2. TM-align: a protein structure alignment algorithm based on the TM-score
3. Protein data bank
4. Direct-coupling analysis of residue coevolution captures native contacts across many protein families
5. LGA: a method for finding 3D similarities in protein structures
6. Identification of direct residue contacts in protein–protein interaction by message passing
7. The Protein Data Bank.
8. HHblits: lightning-fast iterative protein sequence searching by HMM-HMM alignment
9. Basic local alignment search tool.
10. Correlated mutations and residue contacts in proteins

Their papers

• A further leap of improvement in tertiary structure prediction in CASP13 prompts new routes for future assessments (2019) — 70 citations
• Assessment of hard target modeling in CASP12 reveals an emerging role of alignment‐based contact prediction methods (2018) — 90 citations
• Definition and classification of evaluation units for tertiary structure prediction in CASP12 facilitated through semi‐automated metrics (2018) — 14 citations
• Homology- and coevolution-consistent structural models of bacterial copper-tolerance protein CopM support a ‘metal sponge’ function and suggest regions for metal-dependent protein-protein interactions (2015) — 10 citations
• State-of-the-art web services for de novo protein structure prediction (2020) — 17 citations
• How Structural and Physicochemical Determinants Shape Sequence Constraints in a Functional Enzyme (2015) — 43 citations