Ilya A. Vakser

Molecular Biology · 1995–2021

A researcher in the Science corpus: 14 papers; trusts 33 researchers and is trusted by 41 researchers here, as inferred from the citation graph.

Subfields

Whom Ilya A. Vakser trusts overall

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

  1. Yang Zhang
  2. John Moult
  3. Jeffrey Skolnick
  4. Marc F. Lensink
  5. Krzysztof Fidelis
  6. Michael Levitt
  7. Joël Janin
  8. Manfred J. Sippl
  9. Shoshana J. Wodak
  10. Petras J. Kundrotas

Who trusts Ilya A. Vakser overall

  1. D. Ritchie
  2. Ivan V. Anishchenko
  3. Petras J. Kundrotas
  4. Rong Chen
  5. Martin Zacharias
  6. Dina Schneidman-Duhovny
  7. Zhiping Weng
  8. Andriy Kryshtafovych
  9. Yumeng Yan
  10. Inbal Halperin

Papers from Ilya A. Vakser's perspective

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

  1. TM-align: a protein structure alignment algorithm based on the TM-score
  2. Docking and scoring protein complexes: CAPRI 3rd Edition
  3. Optimization of affinity, specificity and function of designed influenza inhibitors using deep sequencing
  4. Distance‐scaled, finite ideal‐gas reference state improves structure‐derived potentials of mean force for structure selection and stability prediction
  5. Molecular surface recognition: determination of geometric fit between proteins and their ligands by correlation techniques.
  6. Assembly of protein tertiary structures from fragments with similar local sequences using simulated annealing and Bayesian scoring functions.
  7. Prediction of homo- and hetero-protein complexes by protein docking and template-based modeling: a CASP-CAPRI experiment
  8. Statistical potential for assessment and prediction of protein structures
  9. Calculation of conformational ensembles from potentials of mean force. An approach to the knowledge-based prediction of local structures in globular proteins.
  10. Robust, high-throughput solution structural analyses by small angle X-ray scattering (SAXS) (Nature Methods)

Their papers