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Gene Expression Regulation

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Identification of differentially expressed genes associated with asthma in children based on the bioanalysis of the regulatory network.

Molecular medicine reports
Asthma, the most common chronic respiratory tract disease in children, is characterized by allergy, recurring airway obstruction and bronchospasm. The aim of the present study was to screen critical differentially expressed genes (DEGs) involved in a...

Genome-wide prediction of cis-regulatory regions using supervised deep learning methods.

BMC bioinformatics
BACKGROUND: In the human genome, 98% of DNA sequences are non-protein-coding regions that were previously disregarded as junk DNA. In fact, non-coding regions host a variety of cis-regulatory regions which precisely control the expression of genes. T...

Heterogeneity Analysis and Diagnosis of Complex Diseases Based on Deep Learning Method.

Scientific reports
Understanding genetic mechanism of complex diseases is a serious challenge. Existing methods often neglect the heterogeneity phenomenon of complex diseases, resulting in lack of power or low reproducibility. Addressing heterogeneity when detecting ep...

Measuring phenotype-phenotype similarity through the interactome.

BMC bioinformatics
BACKGROUND: Recently, measuring phenotype similarity began to play an important role in disease diagnosis. Researchers have begun to pay attention to develop phenotype similarity measurement. However, existing methods ignore the interactions between ...

Transfer Learning for Molecular Cancer Classification Using Deep Neural Networks.

IEEE/ACM transactions on computational biology and bioinformatics
The emergence of deep learning has impacted numerous machine learning based applications and research. The reason for its success lies in two main advantages: 1) it provides the ability to learn very complex non-linear relationships between features ...

Sequential regulatory activity prediction across chromosomes with convolutional neural networks.

Genome research
Models for predicting phenotypic outcomes from genotypes have important applications to understanding genomic function and improving human health. Here, we develop a machine-learning system to predict cell-type-specific epigenetic and transcriptional...

Using deep learning to model the hierarchical structure and function of a cell.

Nature methods
Although artificial neural networks are powerful classifiers, their internal structures are hard to interpret. In the life sciences, extensive knowledge of cell biology provides an opportunity to design visible neural networks (VNNs) that couple the ...

Effect of bone morphogenetic proteins 2 and 4 on survival and development of bovine secondary follicles cultured in vitro.

Theriogenology
This study evaluated the effect of bone morphogenetic proteins 2 (BMP2) and 4 (BMP2) on follicle development and mRNA expression for GDF9, Cyclin B1, BMPR1A, BMPR1B, BMPRII, FSHR and SMAD1 in bovine secondary follicles cultured in vitro. Isolated sec...