AIMC Topic: Gene Regulatory Networks

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Construction of gene-classifier and co-expression network analysis of genes in association with major depressive disorder.

Psychiatry research
Because the pathogenesis of major depressive disorder (MDD) is still unclear and the accurate diagnosis remains unavailable, we aimed to analyze its molecular mechanisms and develop a gene classifier to improve diagnostic accuracy. We extracted diffe...

Classifying Breast Cancer Subtypes Using Deep Neural Networks Based on Multi-Omics Data.

Genes
With the high prevalence of breast cancer, it is urgent to find out the intrinsic difference between various subtypes, so as to infer the underlying mechanisms. Given the available multi-omics data, their proper integration can improve the accuracy o...

LogicNet: probabilistic continuous logics in reconstructing gene regulatory networks.

BMC bioinformatics
BACKGROUND: Gene Regulatory Networks (GRNs) have been previously studied by using Boolean/multi-state logics. While the gene expression values are usually scaled into the range [0, 1], these GRN inference methods apply a threshold to discretize the d...

Association study based on topological constraints of protein-protein interaction networks.

Scientific reports
The non-random interaction pattern of a protein-protein interaction network (PIN) is biologically informative, but its potentials have not been fully utilized in omics studies. Here, we propose a network-permutation-based association study (NetPAS) m...

Selective Neuronal Vulnerability in Alzheimer's Disease: A Network-Based Analysis.

Neuron
A major obstacle to treating Alzheimer's disease (AD) is our lack of understanding of the molecular mechanisms underlying selective neuronal vulnerability, a key characteristic of the disease. Here, we present a framework integrating high-quality neu...

Biosystems Design by Machine Learning.

ACS synthetic biology
Biosystems such as enzymes, pathways, and whole cells have been increasingly explored for biotechnological applications. However, the intricate connectivity and resulting complexity of biosystems poses a major hurdle in designing biosystems with desi...

Machine learning uncovers cell identity regulator by histone code.

Nature communications
Conversion between cell types, e.g., by induced expression of master transcription factors, holds great promise for cellular therapy. Our ability to manipulate cell identity is constrained by incomplete information on cell identity genes (CIGs) and t...

SemanticGO: a tool for gene functional similarity analysis in Arabidopsis thaliana and rice.

Plant science : an international journal of experimental plant biology
Gene or pathway functional similarities are important information for researchers. However, these similarities are often described sparsely and qualitatively. The latent semantic analysis of Arabidopsis thaliana (Arabidopsis) Gene Ontology (GO) data ...