AIMC Topic: Databases, Genetic

Clear Filters Showing 311 to 320 of 747 articles

Drug Resistance Prediction Using Deep Learning Techniques on HIV-1 Sequence Data.

Viruses
The fast replication rate and lack of repair mechanisms of human immunodeficiency virus (HIV) contribute to its high mutation frequency, with some mutations resulting in the evolution of resistance to antiretroviral therapies (ART). As such, studying...

Machine-Learning Prediction of Oral Drug-Induced Liver Injury (DILI) via Multiple Features and Endpoints.

BioMed research international
Drug discovery is a costly process which usually takes more than 10 years and billions of dollars for one successful drug to enter the market. Despite all the safety tests, drugs may still cause adverse reactions and be restricted in use or even with...

RadAtlas 1.0: a knowledgebase focusing on radiation-associated genes.

International journal of radiation biology
Ionizing radiation has very complex biological effects, such as inducing damage to DNA and proteins, ionizing water molecules to produce toxic free radicals, and triggering genetic and somatic effects. Understanding the biomolecular response mechani...

PopPhy-CNN: A Phylogenetic Tree Embedded Architecture for Convolutional Neural Networks to Predict Host Phenotype From Metagenomic Data.

IEEE journal of biomedical and health informatics
Accurate prediction of the host phenotype from a metagenomic sample and identification of the associated microbial markers are important in understanding potential host-microbiome interactions related to disease initiation and progression. We introdu...

Predicting cancer origins with a DNA methylation-based deep neural network model.

PloS one
Cancer origin determination combined with site-specific treatment of metastatic cancer patients is critical to improve patient outcomes. Existing pathology and gene expression-based techniques often have limited performance. In this study, we develop...

SDLDA: lncRNA-disease association prediction based on singular value decomposition and deep learning.

Methods (San Diego, Calif.)
In recent years, accumulating studies have shown that long non-coding RNAs (lncRNAs) not only play an important role in the regulation of various biological processes but also are the foundation for understanding mechanisms of human diseases. Due to ...

Artificial Intelligence Analysis of Gene Expression Data Predicted the Prognosis of Patients with Diffuse Large B-Cell Lymphoma.

The Tokai journal of experimental and clinical medicine
OBJECTIVE: We aimed to identify new biomarkers in Diffuse Large B-cell Lymphoma (DLBCL) using the deep learning technique.

Fold-Change-Specific Enrichment Analysis (FSEA): Quantification of Transcriptional Response Magnitude for Functional Gene Groups.

Genes
Gene expression profiling data contains more information than is routinely extracted with standard approaches. Here we present Fold-Change-Specific Enrichment Analysis (FSEA), a new method for functional annotation of differentially expressed genes f...

Meta-Analysis Based on Nonconvex Regularization.

Scientific reports
The widespread applications of high-throughput sequencing technology have produced a large number of publicly available gene expression datasets. However, due to the gene expression datasets have the characteristics of small sample size, high dimensi...

Stable gene selection by self-representation method in fuzzy sample classification.

Medical & biological engineering & computing
In recent years, microarray technology and gene expression profiles have been widely used to detect, predict, or classify the samples of various diseases. The presence of large genes in these profiles and the small number of samples are known challen...