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High-Throughput Nucleotide Sequencing

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Computational methods and next-generation sequencing approaches to analyze epigenetics data: Profiling of methods and applications.

Methods (San Diego, Calif.)
Epigenetics is mainly comprised of features that regulate genomic interactions thereby playing a crucial role in a vast array of biological processes. Epigenetic mechanisms such as DNA methylation and histone modifications influence gene expression b...

Identification of the human DPR core promoter element using machine learning.

Nature
The RNA polymerase II (Pol II) core promoter is the strategic site of convergence of the signals that lead to the initiation of DNA transcription, but the downstream core promoter in humans has been difficult to understand. Here we analyse the human ...

Sequence-enabled community-based microbial source tracking in surface waters using machine learning classification: A review.

Journal of microbiological methods
The development of Microbial Source Tracking (MST) technologies was borne out of necessity. This was largely due to the: 1) inadequacies of the fecal indicator bacterial paradigm, 2) fact that many fecal bacteria can survive and often grow in the env...

High throughput assessment of biomarkers in tissue microarrays using artificial intelligence: PTEN loss as a proof-of-principle in multi-center prostate cancer cohorts.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Phosphatase and tensin homolog (PTEN) loss is associated with adverse outcomes in prostate cancer and has clinical potential as a prognostic biomarker. The objective of this work was to develop an artificial intelligence (AI) system for automated det...

DeepVariant-on-Spark: Small-Scale Genome Analysis Using a Cloud-Based Computing Framework.

Computational and mathematical methods in medicine
Although sequencing a human genome has become affordable, identifying genetic variants from whole-genome sequence data is still a hurdle for researchers without adequate computing equipment or bioinformatics support. GATK is a gold standard method fo...

Detecting Interactive Gene Groups for Single-Cell RNA-Seq Data Based on Co-Expression Network Analysis and Subgraph Learning.

Cells
High-throughput sequencing technologies have enabled the generation of single-cell RNA-seq (scRNA-seq) data, which explore both genetic heterogeneity and phenotypic variation between cells. Some methods have been proposed to detect the related genes ...

A data-driven approach to build a predictive model of cancer patients' disease outcome by utilizing co-expression networks.

Computers in biology and medicine
BACKGROUND: Next Generation Sequencing (NGS) technologies have revolutionized genomics data research over the last decades by facilitating high-throughput sequencing of genetic material such as RNA Sequencing (RNAseq). A significant challenge is to e...

Deep learning based genome analysis and NGS-RNA LL identification with a novel hybrid model.

Bio Systems
The conventional image segmentation techniques have a lot of issues with highest computational cost and low level accuracy for medical image diagnosis and genome analysis. The deep learning based optimization models utilize to predict the liver cance...