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Sequence Analysis

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Machine learning techniques for sequence-based prediction of viral-host interactions between SARS-CoV-2 and human proteins.

Biomedical journal
BACKGROUND: COVID-19 (Coronavirus Disease-19), a disease caused by the SARS-CoV-2 virus, has been declared as a pandemic by the World Health Organization on March 11, 2020. Over 15 million people have already been affected worldwide by COVID-19, resu...

Deep Neural Networks for Epistatic Sequence Analysis.

Methods in molecular biology (Clifton, N.J.)
We report a step-by-step protocol to use pysster, a TensorFlow-based package for building deep neural networks on a broad range of epistatic sequences such as DNA, RNA, or annotated secondary structure sequences. Pysster provides users comprehensive ...

Genomic sequence analysis of lung infections using artificial intelligence technique.

Interdisciplinary sciences, computational life sciences
Attributable to the modernization of Artificial Intelligence (AI) procedures in healthcare services, various developments including Support Vector Machine (SVM), and profound learning. For example, Convolutional Neural systems (CNN) have prevalently ...

iLearnPlus: a comprehensive and automated machine-learning platform for nucleic acid and protein sequence analysis, prediction and visualization.

Nucleic acids research
Sequence-based analysis and prediction are fundamental bioinformatic tasks that facilitate understanding of the sequence(-structure)-function paradigm for DNAs, RNAs and proteins. Rapid accumulation of sequences requires equally pervasive development...

eSkip-Finder: a machine learning-based web application and database to identify the optimal sequences of antisense oligonucleotides for exon skipping.

Nucleic acids research
Exon skipping using antisense oligonucleotides (ASOs) has recently proven to be a powerful tool for mRNA splicing modulation. Several exon-skipping ASOs have been approved to treat genetic diseases worldwide. However, a significant challenge is the d...

Deep learning of a bacterial and archaeal universal language of life enables transfer learning and illuminates microbial dark matter.

Nature communications
The majority of microbial genomes have yet to be cultured, and most proteins identified in microbial genomes or environmental sequences cannot be functionally annotated. As a result, current computational approaches to describe microbial systems rely...

A tool for feature extraction from biological sequences.

Briefings in bioinformatics
With the advances in sequencing technologies, a huge amount of biological data is extracted nowadays. Analyzing this amount of data is beyond the ability of human beings, creating a splendid opportunity for machine learning methods to grow. The metho...

Automated filtering of genome-wide large deletions through an ensemble deep learning framework.

Methods (San Diego, Calif.)
Computational methods based on whole genome linked-reads and short-reads have been successful in genome assembly and detection of structural variants (SVs). Numerous variant callers that rely on linked-reads and short reads can detect genetic variati...

Alignment-Free Sequence Comparison: A Systematic Survey From a Machine Learning Perspective.

IEEE/ACM transactions on computational biology and bioinformatics
The encounter of large amounts of biological sequence data generated during the last decades and the algorithmic and hardware improvements have offered the possibility to apply machine learning techniques in bioinformatics. While the machine learning...