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Benchmarking Refined and Unrefined AlphaFold2 Structures for Hit Discovery

Yuqi Zhang, Marton Vass, Da Shi, Esam Abualrous, Jenny Chambers, Nikita Chopra, Chris Higgs, Koushik Kasavajhala, Hubert Li, Prajwal Nandekar, Hideyuki Sato, Edward Miller, Matt Repasky, Steven Jerome

Version 2 posted 27 June 2022

2,633

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4

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Biological and Medicinal Chemistry

Working Paper

Improving ΔΔG predictions with a multi-task convolutional Siamese Network

Andrew McNutt, David Koes

Version 1 posted 14 December 2021

610

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Materials Science

Working Paper

Predicting the band gap of binary compounds from machine-learning regression methods

Mengbo Guo, Xuyang Xu, Han Xie

Version 1 posted 21 December 2021

541

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1

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Earth, Space, and Environmental Chemistry

Working Paper

Using machine learning to estimate wildfire PM2.5 at California ZIP codes (2006-2020)

Rosana Aguilera, Nana Luo, Rupa Basu, Jun Wu, Alexander Gershunov, Tarik Benmarhnia

Version 1 posted 19 October 2021

576

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Theoretical and Computational Chemistry

Working Paper

Which molecular properties determine the impact sensitivity of an explosive? A machine learning quantitative investigation of nitroaromatic explosives

Itamar Borges Jr, Júlio César Duarte, Romulo Dias da Rocha

Version 1 posted 15 November 2022

351

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Theoretical and Computational Chemistry

Working Paper

Combining Generative Adversarial Network and First-Principles Based Microkinetics for Heterogeneous Catalyst Design

Atsushi Ishikawa

Version 1 posted 25 October 2021

317

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Analytical Chemistry

Working Paper

Computer Vision for Understanding Catalyst Degradation Kinetics

Chunhui Yan, Megan Cowie, Calum Howcutt, Katherine Wheelhouse, Neil Hodnett, Martin Kollie, Martin Gildea, Martin Goodfellow, Marc Reid

Version 1 posted 10 June 2022

408

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3

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Catalysis

Working Paper

Machine learning prediction of the electronic property of binary transition metal alloys

Yixuan Che, Junyi Zhao, Hao Wang

Version 1 posted 21 December 2021

269

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Theoretical and Computational Chemistry

Working Paper

Filter feature selection for unsupervised clustering of designer drugs using DFT simulated IR spectra data

Kedan He

Version 1 posted 07 September 2021

193

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Catalysis

Working Paper

Predicting Highly Enantioselective Catalysts Using Tunable Fragment Descriptors

Nobuya Tsuji, Pavel Sidorov, Chendan Zhu, Yuuya Nagata, Timur Gimadiev, Alexandre Varnek, Benjamin List

Version 1 posted 29 July 2022

847

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1

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813 results in Machine Learning in Keywords: Machine Learning

Benchmarking Refined and Unrefined AlphaFold2 Structures for Hit Discovery

Improving ΔΔG predictions with a multi-task convolutional Siamese Network

Predicting the band gap of binary compounds from machine-learning regression methods

Using machine learning to estimate wildfire PM2.5 at California ZIP codes (2006-2020)

Which molecular properties determine the impact sensitivity of an explosive? A machine learning quantitative investigation of nitroaromatic explosives

Combining Generative Adversarial Network and First-Principles Based Microkinetics for Heterogeneous Catalyst Design

Computer Vision for Understanding Catalyst Degradation Kinetics

Machine learning prediction of the electronic property of binary transition metal alloys

Filter feature selection for unsupervised clustering of designer drugs using DFT simulated IR spectra data

Predicting Highly Enantioselective Catalysts Using Tunable Fragment Descriptors

813 results in Keywords: Machine Learning