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A Deep Learning Approach to Antibiotic Discovery

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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.
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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.

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DeepPurpose: a deep learning library for drug-target interaction prediction.

TL;DR: DeepPurpose as discussed by the authors is a comprehensive and easy-to-use DL library for drug-target interaction prediction, which supports training of customized DTI prediction models by implementing 15 compound and protein encoders and over 50 neural architectures.
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Artificial Intelligence in the Battle against Coronavirus (COVID-19): A Survey and Future Research Directions

TL;DR: A survey of AI methods being used in various applications in the fight against the COVID-19 outbreak is presented and the crucial roles of AI research in this unprecedented battle are outlined.
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Materials design by synthetic biology

TL;DR: In this paper, the authors discuss synthetic-biology tools, including genetic circuits, model organisms and design parameters, which can be applied for the construction of smart living materials, such as self-organizing functional materials.
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Antibiotic resistance and persistence-Implications for human health and treatment perspectives.

TL;DR: This review focuses on bacterial mechanisms allowing evasion of antibiotic killing and discusses their implications on human health, including the relationship between antibiotic persistence and bacterial heterogeneity, and discusses recent studies that link bacterial persistence and tolerance with the evolution of antibiotic resistance.
References
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Journal ArticleDOI

Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

TL;DR: This work presents DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates, which enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression.
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Fast and accurate short read alignment with Burrows–Wheeler transform

TL;DR: Burrows-Wheeler Alignment tool (BWA) is implemented, a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps.
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edgeR: a Bioconductor package for differential expression analysis of digital gene expression data.

TL;DR: EdgeR as mentioned in this paper is a Bioconductor software package for examining differential expression of replicated count data, which uses an overdispersed Poisson model to account for both biological and technical variability and empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference.
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One-step inactivation of chromosomal genes in Escherichia coli K-12 using PCR products

TL;DR: A simple and highly efficient method to disrupt chromosomal genes in Escherichia coli in which PCR primers provide the homology to the targeted gene(s), which should be widely useful, especially in genome analysis of E. coli and other bacteria.
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Extended-Connectivity Fingerprints

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.
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