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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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Efficient Conformal Prediction via Cascaded Inference with Expanded Admission.

TL;DR: In this article, a set of promising prediction candidates is identified in place of a single prediction, which is guaranteed to contain a correct answer with high probability, and is well suited for many open-ended classification tasks.
Journal ArticleDOI

Accelerating Antimicrobial Peptide Discovery with Latent Sequence-Structure Model

Danqing Wang, +3 more
- 28 Nov 2022 - 
TL;DR: Wang et al. as discussed by the authors proposed a latent sequence-structure model for AMPs (LSSAMP) with multi-scale VQ-VAE to incorporate secondary structures, which can simultaneously generate peptides with ideal sequence attributes and secondary structures.
Proceedings ArticleDOI

Prediction of Potential Natural Antibiotics based on Jamu Formula Using Machine Learning Approach

TL;DR: In this article , the authors explored the utility of Jamu ingredients on the molecular level to predict new natural antibiotic candidates and extracted the potential compounds based on the best model as candidate antibiotics corresponding to five groups of efficacies, e.g., digestive systems, respiratory systems, reproductive systems, skin and soft tissue, and urinary systems.
Journal ArticleDOI

Accelerating Backward Aggregation in GCN Training With Execution Path Preparing on GPUs

TL;DR: In this article , the authors propose an execution path preparing method that collects and coalesces the data used during backward propagations of GCN training conducted on GPUs, which can be used either before the training or on-the-fly with the training.
Journal ArticleDOI

A novel framework integrating AI model and enzymological experiments promotes identification of SARS-CoV-2 3CL protease inhibitors and activity-based probe.

TL;DR: AIMEE as discussed by the authors integrates deep learning and enzymological experiments to identify inhibitors against 3CL protease of SARS-CoV-2 (Severe acute respiratory syndrome coronavirus 2), which has taken a significant toll on people across the globe.
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.
Journal ArticleDOI

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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