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Phylogeny

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Identification of B cell subsets based on antigen receptor sequences using deep learning.

Frontiers in immunology
B cell receptors (BCRs) denote antigen specificity, while corresponding cell subsets indicate B cell functionality. Since each B cell uniquely encodes this combination, physical isolation and subsequent processing of individual B cells become indispe...

Analysis of Emerging Variants of Turkey Reovirus using Machine Learning.

Briefings in bioinformatics
Avian reoviruses continue to cause disease in turkeys with varied pathogenicity and tissue tropism. Turkey enteric reovirus has been identified as a causative agent of enteritis or inapparent infections in turkeys. The new emerging variants of turkey...

DSNetax: a deep learning species annotation method based on a deep-shallow parallel framework.

Briefings in bioinformatics
Microbial community analysis is an important field to study the composition and function of microbial communities. Microbial species annotation is crucial to revealing microorganisms' complex ecological functions in environmental, ecological and host...

Improving the performance of supervised deep learning for regulatory genomics using phylogenetic augmentation.

Bioinformatics (Oxford, England)
MOTIVATION: Supervised deep learning is used to model the complex relationship between genomic sequence and regulatory function. Understanding how these models make predictions can provide biological insight into regulatory functions. Given the compl...

Harnessing artificial intelligence-driven approach for enhanced indole-3-acetic acid from the newly isolated Streptomyces rutgersensis AW08.

Environmental research
Indole-3-acetic acid (IAA) derived from Actinobacteria fermentations on agro-wastes constitutes a safer and low-cost alternative to synthetic IAA. This study aims to select a high IAA-producing Streptomyces-like strain isolated from Lake Oubeira sedi...

DeepDynaForecast: Phylogenetic-informed graph deep learning for epidemic transmission dynamic prediction.

PLoS computational biology
In the midst of an outbreak or sustained epidemic, reliable prediction of transmission risks and patterns of spread is critical to inform public health programs. Projections of transmission growth or decline among specific risk groups can aid in opti...

Genomic language model predicts protein co-regulation and function.

Nature communications
Deciphering the relationship between a gene and its genomic context is fundamental to understanding and engineering biological systems. Machine learning has shown promise in learning latent relationships underlying the sequence-structure-function par...

A culture-independent approach, supervised machine learning, and the characterization of the microbial community composition of coastal areas across the Bay of Bengal and the Arabian Sea.

BMC microbiology
BACKGROUND: Coastal areas are subject to various anthropogenic and natural influences. In this study, we investigated and compared the characteristics of two coastal regions, Andhra Pradesh (AP) and Goa (GA), focusing on pollution, anthropogenic acti...

A machine-learning-based alternative to phylogenetic bootstrap.

Bioinformatics (Oxford, England)
MOTIVATION: Currently used methods for estimating branch support in phylogenetic analyses often rely on the classic Felsenstein's bootstrap, parametric tests, or their approximations. As these branch support scores are widely used in phylogenetic ana...

Deep learning for predicting 16S rRNA gene copy number.

Scientific reports
Culture-independent 16S rRNA gene metabarcoding is a commonly used method for microbiome profiling. To achieve more quantitative cell fraction estimates, it is important to account for the 16S rRNA gene copy number (hereafter 16S GCN) of different co...