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WIREs Comput Mol Sci
Impact Factor: 25.113
Wiley Interdisciplinary Reviews:
WIREs Computational Molecular Science
Volume 11 Issue 1 (January 2021)
Page 0 - 0

Cover Image

Cover Image, Volume 11, Issue 1
Published Online: Dec 11 2020
DOI: 10.1002/wcms.1507
The cover image is based on the Focus Article Advances in the prediction of mouse liver microsomal studies: From machine learning to deep learning by Alex Renn et al., https://doi.org/10.1002/wcms.1479.
Abstract Full article on Wiley Online Library:   HTML | PDF

Advanced Reviews

High‐throughput computational materials screening and discovery of optoelectronic semiconductors
Published Online: Jun 29 2020
DOI: 10.1002/wcms.1489
We herein reviewed the recent progress on high‐throughput computational screening of optoelectronic semiconductors, with focus on photovoltaic solar absorbers, photoelectrochemical cells, semiconductor light‐emitting diodes, and transparent conducting materials. The general workflow of high‐throughput computational screening, released workhorse infrastructures, and generated material databases were also summarized.
Abstract Full article on Wiley Online Library:   HTML | PDF
On the top rung of Jacob's ladder of density functional theory: Toward resolving the dilemma of SIE and NCE
Published Online: Jun 23 2020
DOI: 10.1002/wcms.1490
Jacob's Ladder of DFT towards Chemical Accuracy.
Abstract Full article on Wiley Online Library:   HTML | PDF
DFTpy: An efficient and object‐oriented platform for orbital‐free DFT simulations
Published Online: Jun 19 2020
DOI: 10.1002/wcms.1482
Release of DFTpy version 1.0.
Abstract Full article on Wiley Online Library:   HTML | PDF
The prospects of quantum computing in computational molecular biology
Published Online: May 22 2020
DOI: 10.1002/wcms.1481
Quantum computers promise faster algorithms that can affect molecular biology and bioinformatics – for example, in data analysis, electronic structure simulations and protein modeling.
Abstract Full article on Wiley Online Library:   HTML | PDF
Machine‐learning scoring functions for structure‐based virtual screening
Published Online: Apr 22 2020
DOI: 10.1002/wcms.1478
Machine‐learning scoring functions are able to discover mid‐nanomolar leads with novel chemical scaffolds directly from rescoring docked poses, outperforming classical scoring functions at structure‐based virtual screening, either retrospectively or prospectively.
Abstract Full article on Wiley Online Library:   HTML | PDF

Focus Article

Advances in the prediction of mouse liver microsomal studies: From machine learning to deep learning
Published Online: Apr 30 2020
DOI: 10.1002/wcms.1479
By bypassing the necessity for manual feature extraction, graph convolution networks can achieve an unprecedented level of accuracy over other machine learning methods used in the past.
Abstract Full article on Wiley Online Library:   HTML | PDF

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