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High-Throughput Nucleotide Sequencing

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Next-Generation Global Biomonitoring: Large-scale, Automated Reconstruction of Ecological Networks.

Trends in ecology & evolution
We foresee a new global-scale, ecological approach to biomonitoring emerging within the next decade that can detect ecosystem change accurately, cheaply, and generically. Next-generation sequencing of DNA sampled from the Earth's environments would p...

DNA methylation-based forensic age prediction using artificial neural networks and next generation sequencing.

Forensic science international. Genetics
The ability to estimate the age of the donor from recovered biological material at a crime scene can be of substantial value in forensic investigations. Aging can be complex and is associated with various molecular modifications in cells that accumul...

Imputation for transcription factor binding predictions based on deep learning.

PLoS computational biology
Understanding the cell-specific binding patterns of transcription factors (TFs) is fundamental to studying gene regulatory networks in biological systems, for which ChIP-seq not only provides valuable data but is also considered as the gold standard....

PaPrBaG: A machine learning approach for the detection of novel pathogens from NGS data.

Scientific reports
The reliable detection of novel bacterial pathogens from next-generation sequencing data is a key challenge for microbial diagnostics. Current computational tools usually rely on sequence similarity and often fail to detect novel species when closely...

Prediction of Protein-Protein Interactions by Evidence Combining Methods.

International journal of molecular sciences
Most cellular functions involve proteins' features based on their physical interactions with other partner proteins. Sketching a map of protein-protein interactions (PPIs) is therefore an important inception step towards understanding the basics of c...

SNooPer: a machine learning-based method for somatic variant identification from low-pass next-generation sequencing.

BMC genomics
BACKGROUND: Next-generation sequencing (NGS) allows unbiased, in-depth interrogation of cancer genomes. Many somatic variant callers have been developed yet accurate ascertainment of somatic variants remains a considerable challenge as evidenced by t...

WORMHOLE: Novel Least Diverged Ortholog Prediction through Machine Learning.

PLoS computational biology
The rapid advancement of technology in genomics and targeted genetic manipulation has made comparative biology an increasingly prominent strategy to model human disease processes. Predicting orthology relationships between species is a vital componen...

Integrated gene set analysis for microRNA studies.

Bioinformatics (Oxford, England)
MOTIVATION: Functional interpretation of miRNA expression data is currently done in a three step procedure: select differentially expressed miRNAs, find their target genes, and carry out gene set overrepresentation analysis Nevertheless, major limita...

tarSVM: Improving the accuracy of variant calls derived from microfluidic PCR-based targeted next generation sequencing using a support vector machine.

BMC bioinformatics
BACKGROUND: Targeted sequencing of discrete gene sets is a cost effective strategy to screen subjects for monogenic forms of disease. One method to achieve this pairs microfluidic PCR with next generation sequencing. The PCR step of this pipeline cre...

DiscMLA: An Efficient Discriminative Motif Learning Algorithm over High-Throughput Datasets.

IEEE/ACM transactions on computational biology and bioinformatics
The transcription factors (TFs) can activate or suppress gene expression by binding to specific sites, hence are crucial regulatory elements for transcription. Recently, series of discriminative motif finders have been tailored to offering promising ...