AIMC Topic: Gene Regulatory Networks

Clear Filters Showing 621 to 630 of 830 articles

Confirming an integrated pathology of diabetes and its complications by molecular biomarker-target network analysis.

Molecular medicine reports
Despite ongoing research into diabetes and its complications, the underlying molecular associations remain to be elucidated. The systematic identification of molecular interactions in associated diseases may be approached using a network analysis str...

Integrated gene set analysis for microRNA studies.

Bioinformatics (Oxford, England)
MOTIVATION: Functional interpretation of miRNA expression data is currently done in a three step procedure: select differentially expressed miRNAs, find their target genes, and carry out gene set overrepresentation analysis Nevertheless, major limita...

A knowledge-based approach for predicting gene-disease associations.

Bioinformatics (Oxford, England)
MOTIVATION: Recent advances of next-generation sequence technologies have made it possible to rapidly and inexpensively identify gene variations. Knowing the disease association of these gene variations is important for early intervention to treat de...

Neural model of gene regulatory network: a survey on supportive meta-heuristics.

Theory in biosciences = Theorie in den Biowissenschaften
Gene regulatory network (GRN) is produced as a result of regulatory interactions between different genes through their coded proteins in cellular context. Having immense importance in disease detection and drug finding, GRN has been modelled through ...

LS-GKM: a new gkm-SVM for large-scale datasets.

Bioinformatics (Oxford, England)
UNLABELLED: gkm-SVM is a sequence-based method for predicting and detecting the regulatory vocabulary encoded in functional DNA elements, and is a commonly used tool for studying gene regulatory mechanisms. Here we introduce new software, LS-GKM, whi...

Mixed Integer Linear Programming based machine learning approach identifies regulators of telomerase in yeast.

Nucleic acids research
Understanding telomere length maintenance mechanisms is central in cancer biology as their dysregulation is one of the hallmarks for immortalization of cancer cells. Important for this well-balanced control is the transcriptional regulation of the te...

Network stratification analysis for identifying function-specific network layers.

Molecular bioSystems
A major challenge of systems biology is to capture the rewiring of biological functions (e.g. signaling pathways) in a molecular network. To address this problem, we proposed a novel computational framework, namely network stratification analysis (Ne...

ZeitZeiger: supervised learning for high-dimensional data from an oscillatory system.

Nucleic acids research
Numerous biological systems oscillate over time or space. Despite these oscillators' importance, data from an oscillatory system is problematic for existing methods of regularized supervised learning. We present ZeitZeiger, a method to predict a peri...

Extending gene ontology with gene association networks.

Bioinformatics (Oxford, England)
MOTIVATION: Gene ontology (GO) is a widely used resource to describe the attributes for gene products. However, automatic GO maintenance remains to be difficult because of the complex logical reasoning and the need of biological knowledge that are no...