AIMC Topic: Databases, Genetic

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Deep learning approach for predicting functional Z-DNA regions using omics data.

Scientific reports
Computational methods to predict Z-DNA regions are in high demand to understand the functional role of Z-DNA. The previous state-of-the-art method Z-Hunt is based on statistical mechanical and energy considerations about B- to Z-DNA transition using ...

Biological interpretation of deep neural network for phenotype prediction based on gene expression.

BMC bioinformatics
BACKGROUND: The use of predictive gene signatures to assist clinical decision is becoming more and more important. Deep learning has a huge potential in the prediction of phenotype from gene expression profiles. However, neural networks are viewed as...

Learning and interpreting the gene regulatory grammar in a deep learning framework.

PLoS computational biology
Deep neural networks (DNNs) have achieved state-of-the-art performance in identifying gene regulatory sequences, but they have provided limited insight into the biology of regulatory elements due to the difficulty of interpreting the complex features...

Scalable classification of organisms into a taxonomy using hierarchical supervised learners.

Journal of bioinformatics and computational biology
Accurately identifying organisms based on their partially available genetic material is an important task to explore the phylogenetic diversity in an environment. Specific fragments in the DNA sequence of a living organism have been defined as DNA ba...

Correlations Between Phenotypes and Biological Process Ontologies in Monogenic Human Diseases.

Interdisciplinary sciences, computational life sciences
A substantial body of research is focused to improve the understanding of the relationship between genotypes and phenotypes. Genotype-phenotype studies have shown promise in improving disease diagnosis in humans and identification of specific clinica...

A Comprehensive Analysis of MicroRNAs in Human Osteoporosis.

Frontiers in endocrinology
MicroRNAs (miRNAs) are single-stranded RNA molecules that control gene expression in various processes, such as cancers, Alzheimer's disease, and bone metabolic diseases. However, the regulatory roles of miRNAs in osteoporosis have not been systemati...

Machine learning analysis of DNA methylation in a hypoxia-immune model of oral squamous cell carcinoma.

International immunopharmacology
BACKGROUND: Hypoxia status and immunity are related with the development and prognosis of oral squamous cell carcinoma (OSCC). Here, we constructed a hypoxia-immune model to explore its upstream mechanism and identify potential CpG sites.

Identification and Classification of Enhancers Using Dimension Reduction Technique and Recurrent Neural Network.

Computational and mathematical methods in medicine
Enhancers are noncoding fragments in DNA sequences, which play an important role in gene transcription and translation. However, due to their high free scattering and positional variability, the identification and classification of enhancers have a h...

CUP-AI-Dx: A tool for inferring cancer tissue of origin and molecular subtype using RNA gene-expression data and artificial intelligence.

EBioMedicine
BACKGROUND: Cancer of unknown primary (CUP), representing approximately 3-5% of all malignancies, is defined as metastatic cancer where a primary site of origin cannot be found despite a standard diagnostic workup. Because knowledge of a patient's pr...

Graph-based exploitation of gene ontology using GOxploreR for scrutinizing biological significance.

Scientific reports
Gene ontology (GO) is an eminent knowledge base frequently used for providing biological interpretations for the analysis of genes or gene sets from biological, medical and clinical problems. Unfortunately, the interpretation of such results is chall...