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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Everything is Connected: Graph Neural Networks
TL;DR: Graph representation learning has been studied extensively in the literature as discussed by the authors , where the main aim is to assimilate the key concepts in the area, and position graph representation learning in a proper context with related fields.
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Machine learning optimization of candidate antibody yields highly diverse sub-nanomolar affinity antibody libraries
Lin Li,Esther Gupta,J. Spaeth,L.S.W. Li Vong Shing,Rafael Gómez Jaimes,Rajmonda S. Caceres,Tristan Bepler,Matthew Walsh +7 more
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Chemistry Inspired Molecular Representation for Property Prediction
TL;DR: In this paper , a molecular representation approach using the concept of functional groups in chemistry is proposed, which is then used for predicting molecular properties and compared with the state-of-the-art deep learning model.
Novel prediction methods for virtual drug screening
TL;DR: Only in the past few years with increases in computing power have researchers really started to embrace the potential of neural networks in various stages of the drug discovery process and promise great perspective in the future development of drug discovery.
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Predictions, Pivots, and a Pandemic: a Review of 2020's Top Translational Bioinformatics Publications.
TL;DR: In this article, the authors provide an overview of emerging themes and notable papers which were published in 2020 in the field of Bioinformatics and Translational Informatics (BTI) for the IMA Yearbook.
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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.