A Deep Learning Approach to Antibiotic Discovery
Jonathan M. Stokes,Kevin Yang,Kyle Swanson,Wengong Jin,Andres Cubillos-Ruiz,Nina M. Donghia,Craig R. MacNair,Shawn French,Lindsey A. Carfrae,Zohar Bloom-Ackermann,Victoria M. Tran,Anush Chiappino-Pepe,Ahmed H. Badran,Ian W. Andrews,Ian W. Andrews,Ian W. Andrews,Emma J. Chory,George M. Church,Eric D. Brown,Tommi S. Jaakkola,Regina Barzilay,James J. Collins +21 more
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TLDR
A deep neural network capable of predicting molecules with antibacterial activity is trained and a molecule from the Drug Repurposing Hub-halicin- is discovered that is structurally divergent from conventional antibiotics and displays bactericidal activity against a wide phylogenetic spectrum of pathogens.About:
This article is published in Cell.The article was published on 2020-02-20 and is currently open access. It has received 1002 citations till now.read more
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Proceedings ArticleDOI
An End-to-end Oxford Nanopore Basecaller Using Convolution-augmented Transformer
TL;DR: CATCaller as mentioned in this paper is an open-source base calling method, which combines global context through Attention and modeling local dependencies through dynamic convolution, and it is shown to consistently outperform the ONT default basecaller Albacore, Guppy, and a recently developed attention-based method SACall in read accuracy.
Journal ArticleDOI
Global Property Prediction: A Benchmark Study on Open-Source, Perovskite-like Datasets.
Felix Mayr,Alessio Gagliardi +1 more
TL;DR: In this paper, a comprehensive comparison of structural fingerprint-based machine learning models on seven open-source databases of perovskite-like materials to predict band gaps and energies is presented.
Graph Adversarial Networks: Protecting Information against Adversarial Attacks
Peiyuan Liao,Han Zhao,Keyulu Xu,Tommi S. Jaakkola,Geoff Gordon,Stefanie Jegelka,Ruslan Salakhutdinov +6 more
TL;DR: A minimax game between the desired GNN encoder and the worst-case attacker is proposed, and the resulting adversarial training creates a strong defense against inference attacks, while only suffering small loss in task performance.
Journal ArticleDOI
Using computers to ESKAPE the antibiotic resistance crisis.
TL;DR: In this article, the authors provide an overview of the implementation of current in-silico state-of-the-art techniques, including machine learning (ML) and deep learning (DL), in drug discovery.
References
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Extended-Connectivity Fingerprints
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TL;DR: A description of their implementation has not previously been presented in the literature, and ECFPs can be very rapidly calculated and can represent an essentially infinite number of different molecular features.