Wiley Interdisciplinary Reviews-Computational Molecular Science

Papers
(The H4-Index of Wiley Interdisciplinary Reviews-Computational Molecular Science is 31. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2021-12-01 to 2025-12-01.)
ArticleCitations
3567
Issue Information280
Quantitative analysis of high‐throughput biological data245
Time‐dependent coupled‐cluster theory193
Theoretical Studies of Molecular Reactions at the Air–Water Interface: Recent Progress and Perspective181
Recent advances in deep learning for retrosynthesis142
Two decades of Martini: Better beads, broader scope131
Cover Image, Volume 12, Issue 5114
Issue Information106
Using machine‐learning‐driven approaches to boost hot‐spot's knowledge73
Small molecule superposition: A comprehensive overview on pose scoring of the latest methods73
Computation of Time‐Resolved Nonlinear Electronic Spectra From Classical Trajectories61
Cover Image, Volume 12, Issue 159
Correction to “ ByteQC : GPU ‐Accelerated Quantum Chemistry Package for Large‐Scale Systems”58
UniversalQM/MMapproaches for general nanoscale applications51
45
Computational methods for unlocking the secrets of potassium channels: Structure, mechanism, and drug design43
Advanced quantum and semiclassical methods for simulating photoinduced molecular dynamics and spectroscopy41
Building Nucleosome Positioning Maps: Discovering Hidden Gems41
39
38
Enhanced sampling strategies for molecular simulation of DNA38
A promising intersection of excited‐state‐specific methods from quantum chemistry and quantum Monte Carlo36
Graph neural networks for conditional de novo drug design34
34
Pre‐exascale HPC approaches for molecular dynamics simulations. Covid‐19 research: A use case34
Issue Information33
Cover Image, Volume 15, Issue 233
Condensed‐Phase Quantum Chemistry32
Enhancing GPU‐Acceleration in the Python‐Based Simulations of Chemistry Frameworks31
Machine learning solutions for predicting protein–protein interactions31
0.1370370388031