AIMC Topic: Databases, Genetic

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Machine Learning Analysis of Naïve B-Cell Receptor Repertoires Stratifies Celiac Disease Patients and Controls.

Frontiers in immunology
Celiac disease (CeD) is a common autoimmune disorder caused by an abnormal immune response to dietary gluten proteins. The disease has high heritability. HLA is the major susceptibility factor, and the HLA effect is mediated via presentation of deami...

seqQscorer: automated quality control of next-generation sequencing data using machine learning.

Genome biology
Controlling quality of next-generation sequencing (NGS) data files is a necessary but complex task. To address this problem, we statistically characterize common NGS quality features and develop a novel quality control procedure involving tree-based ...

Machine Learning Identifies Complicated Sepsis Course and Subsequent Mortality Based on 20 Genes in Peripheral Blood Immune Cells at 24 H Post-ICU Admission.

Frontiers in immunology
A complicated clinical course for critically ill patients admitted to the intensive care unit (ICU) usually includes multiorgan dysfunction and subsequent death. Owing to the heterogeneity, complexity, and unpredictability of the disease progression,...

4mCPred-CNN-Prediction of DNA N4-Methylcytosine in the Mouse Genome Using a Convolutional Neural Network.

Genes
Among DNA modifications, N4-methylcytosine (4mC) is one of the most significant ones, and it is linked to the development of cell proliferation and gene expression. To know different its biological functions, the accurate detection of 4mC sites is re...

Apache Spark based kernelized fuzzy clustering framework for single nucleotide polymorphism sequence analysis.

Computational biology and chemistry
This paper introduces a kernel based fuzzy clustering approach to deal with the non-linear separable problems by applying kernel Radial Basis Functions (RBF) which maps the input data space non-linearly into a high-dimensional feature space. Discover...

Creating artificial human genomes using generative neural networks.

PLoS genetics
Generative models have shown breakthroughs in a wide spectrum of domains due to recent advancements in machine learning algorithms and increased computational power. Despite these impressive achievements, the ability of generative models to create re...

Cross-species Data Classification by Domain Adaptation via Discriminative Heterogeneous Maximum Mean Discrepancy.

IEEE/ACM transactions on computational biology and bioinformatics
Cross-species or Cross-platform data classification is a challenging problem in the field of bioinformatics, which aims to classify data samples in one species/platform by using labeled data samples in another species/platform. Traditional classifica...

ES-ARCNN: Predicting enhancer strength by using data augmentation and residual convolutional neural network.

Analytical biochemistry
Enhancers are non-coding DNA sequences bound by proteins called transcription factors. They function as distant regulators of gene transcription and participate in the development and maintenance of cell types and tissues. Since experimental validati...

HDG-select: A novel GUI based application for gene selection and classification in high dimensional datasets.

PloS one
The selection and classification of genes is essential for the identification of related genes to a specific disease. Developing a user-friendly application with combined statistical rigor and machine learning functionality to help the biomedical res...