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Viruses

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Machine Learning for detection of viral sequences in human metagenomic datasets.

BMC bioinformatics
BACKGROUND: Detection of highly divergent or yet unknown viruses from metagenomics sequencing datasets is a major bioinformatics challenge. When human samples are sequenced, a large proportion of assembled contigs are classified as "unknown", as conv...

Targeting Virus-host Protein Interactions: Feature Extraction and Machine Learning Approaches.

Current drug metabolism
BACKGROUND: Targeting critical viral-host Protein-Protein Interactions (PPIs) has enormous application prospects for therapeutics. Using experimental methods to evaluate all possible virus-host PPIs is labor-intensive and time-consuming. Recent growt...

VHost-Classifier: virus-host classification using natural language processing.

Bioinformatics (Oxford, England)
MOTIVATION: When analyzing viral metagenomic sequences, it is often desired to filter the results of a BLAST analysis by the host species of the virus. VHost-Classifier automates this procedure using a natural language processing algorithm written in...

IILLS: predicting virus-receptor interactions based on similarity and semi-supervised learning.

BMC bioinformatics
BACKGROUND: Viral infectious diseases are the serious threat for human health. The receptor-binding is the first step for the viral infection of hosts. To more effectively treat human viral infectious diseases, the hidden virus-receptor interactions ...

Predicting host taxonomic information from viral genomes: A comparison of feature representations.

PLoS computational biology
The rise in metagenomics has led to an exponential growth in virus discovery. However, the majority of these new virus sequences have no assigned host. Current machine learning approaches to predicting virus host interactions have a tendency to focus...

Virus identification in electron microscopy images by residual mixed attention network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Virus identification in electron microscopy (EM) images is considered as one of the front-line method in pathogen diagnosis and re-emerging infectious agents. However, the existing methods either focused on the detection of ...

Application of machine learning methods to pathogen safety evaluation in biological manufacturing processes.

Biotechnology progress
The production of recombinant therapeutic proteins from animal or human cell lines entails the risk of endogenous viral contamination from cell substrates and adventitious agents from raw materials and environment. One of the approaches to control su...

VIDHOP, viral host prediction with deep learning.

Bioinformatics (Oxford, England)
MOTIVATION: Zoonosis, the natural transmission of infections from animals to humans, is a far-reaching global problem. The recent outbreaks of Zikavirus, Ebolavirus and Coronavirus are examples of viral zoonosis, which occur more frequently due to gl...

Accurate prediction of multi-label protein subcellular localization through multi-view feature learning with RBRL classifier.

Briefings in bioinformatics
Multi-label proteins can participate in carrier transportation, enzyme catalysis, hormone regulation and other life activities. Meanwhile, they play a key role in the fields of biopharmaceuticals, gene and cell therapy. This article proposes a predic...

RNN-VirSeeker: A Deep Learning Method for Identification of Short Viral Sequences From Metagenomes.

IEEE/ACM transactions on computational biology and bioinformatics
Viruses are the most abundant biological entities on earth, and play vital roles in many aspects of microbial communities. As major human pathogens, viruses have caused huge mortality and morbidity to human society in history. Metagenomic sequencing ...