Juan M. Lavista Ferres

Molecular Biology · with Borowsky · 2022–2023

A researcher in the Science corpus: 2 papers; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 44 citations into it
• Materials Chemistry — 18 citations into it
• Computational Biology & Bioinformatics — 16 citations into it
• Spectroscopy — 7 citations into it

Whom Juan M. Lavista Ferres trusts overall

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

1. Wen Torng

Papers from Juan M. Lavista Ferres's perspective

Ordered by how strongly the researchers Juan M. Lavista Ferres trusts endorse each paper. Same corpus, a different order for every researcher.

1. Protein data bank
2. 3D deep convolutional neural networks for amino acid environment similarity analysis
3. Highly accurate protein structure prediction with AlphaFold
4. Design of a Novel Globular Protein Fold with Atomic-Level Accuracy
5. De novo design of a four-fold symmetric TIM-barrel protein with atomic-level accuracy
6. A point‐charge force field for molecular mechanics simulations of proteins based on condensed‐phase quantum mechanical calculations (Journal of Computational Chemistry)
7. Accurate prediction of protein structures and interactions using a 3-track neural network (Science)
8. The Protein Data Bank
9. GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers
10. Biopython: freely available Python tools for computational molecular biology and bioinformatics

Their papers

• Predicting the locations of cryptic pockets from single protein structures using the PocketMiner graph neural network (2022) — 69 citations
• Predicting locations of cryptic pockets from single protein structures using the PocketMiner graph neural network (2023) — 109 citations