AIMC Topic: Gene Regulatory Networks

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Dual Convolutional Neural Network Based Method for Predicting Disease-Related miRNAs.

International journal of molecular sciences
Identification of disease-related microRNAs (disease miRNAs) is helpful for understanding and exploring the etiology and pathogenesis of diseases. Most of recent methods predict disease miRNAs by integrating the similarities and associations of miRNA...

Gene Ontology-based function prediction of long non-coding RNAs using bi-random walk.

BMC medical genomics
BACKGROUND: With the development of sequencing technology, more and more long non-coding RNAs (lncRNAs) have been identified. Some lncRNAs have been confirmed that they play an important role in the process of development through the dosage compensat...

Systems Biology and Machine Learning in Plant-Pathogen Interactions.

Molecular plant-microbe interactions : MPMI
Systems biology is an inclusive approach to study the static and dynamic emergent properties on a global scale by integrating multiomics datasets to establish qualitative and quantitative associations among multiple biological components. With an abu...

Generalized multifactor dimensionality reduction approaches to identification of genetic interactions underlying ordinal traits.

Genetic epidemiology
The manifestation of complex traits is influenced by gene-gene and gene-environment interactions, and the identification of multifactor interactions is an important but challenging undertaking for genetic studies. Many complex phenotypes such as dise...

Gene Regulatory Relationship Mining Using Improved Three-Phase Dependency Analysis Approach.

IEEE/ACM transactions on computational biology and bioinformatics
How to mine the gene regulatory relationship and construct gene regulatory network (GRN) is of utmost interest within the whole biological community, however, which has been consistently a challenging problem since the tremendous complexity in cellul...

WEADE: A workflow for enrichment analysis and data exploration.

PloS one
Data analysis based on enrichment of Gene Ontology terms has become an important step in exploring large gene or protein expression datasets and several stand-alone or web tools exist for that purpose. However, a comprehensive and consistent analysis...

Gene ontology enrichment analysis of congenital diaphragmatic hernia-associated genes.

Pediatric research
Congenital diaphragmatic hernia (CDH) is a commonly occurring major congenital anomaly with a profound impact on neonatal mortality. The etiology of CDH is poorly understood and is complicated by multiple clinical presentations, reflecting the locati...

Initial state perturbations as a validation method for data-driven fuzzy models of cellular networks.

BMC bioinformatics
BACKGROUND: Data-driven methods that automatically learn relations between attributes from given data are a popular tool for building mathematical models in computational biology. Since measurements are prone to errors, approaches dealing with uncert...

G2Vec: Distributed gene representations for identification of cancer prognostic genes.

Scientific reports
Identification of cancer prognostic genes is important in that it can lead to accurate outcome prediction and better therapeutic trials for cancer patients. Many computational approaches have been proposed to achieve this goal; however, there is room...