AIMC Topic: Gene Regulatory Networks

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FMLNCSIM: fuzzy measure-based lncRNA functional similarity calculation model.

Oncotarget
Accumulating experimental studies have indicated the influence of lncRNAs on various critical biological processes as well as disease development and progression. Calculating lncRNA functional similarity is of high value in inferring lncRNA functions...

Structural Comparison of Gene Relevance Networks for Breast Cancer Tissues in Different Grades.

Combinatorial chemistry & high throughput screening
BACKGROUND: The breast is an important biological system of human with two distinct states, i.e. normal and tumoral. Research on breast cancer could be based on systematic modeling to contrast the system structures of these two states.

KNOWLEDGE-ASSISTED APPROACH TO IDENTIFY PATHWAYS WITH DIFFERENTIAL DEPENDENCIES.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
We have previously developed a statistical method to identify gene sets enriched with condition-specific genetic dependencies. The method constructs gene dependency networks from bootstrapped samples in one condition and computes the divergence betwe...

LncRNA ontology: inferring lncRNA functions based on chromatin states and expression patterns.

Oncotarget
Accumulating evidences suggest that long non-coding RNAs (lncRNAs) perform important functions. Genome-wide chromatin-states area rich source of information about cellular state, yielding insights beyond what is typically obtained by transcriptome pr...

Semi-supervised prediction of gene regulatory networks using machine learning algorithms.

Journal of biosciences
Use of computational methods to predict gene regulatory networks (GRNs) from gene expression data is a challenging task. Many studies have been conducted using unsupervised methods to fulfill the task; however, such methods usually yield low predicti...

Identification of a Selective G1-Phase Benzimidazolone Inhibitor by a Senescence-Targeted Virtual Screen Using Artificial Neural Networks.

Neoplasia (New York, N.Y.)
Cellular senescence is a barrier to tumorigenesis in normal cells, and tumor cells undergo senescence responses to genotoxic stimuli, which is a potential target phenotype for cancer therapy. However, in this setting, mixed-mode responses are common ...

Exploiting ontology graph for predicting sparsely annotated gene function.

Bioinformatics (Oxford, England)
MOTIVATION: Systematically predicting gene (or protein) function based on molecular interaction networks has become an important tool in refining and enhancing the existing annotation catalogs, such as the Gene Ontology (GO) database. However, functi...

Identification of hepatocellular carcinoma-related genes with a machine learning and network analysis.

Journal of computational biology : a journal of computational molecular cell biology
Liver cancer is one of the leading causes of cancer mortality worldwide. Hepatocellular carcinoma (HCC) is the main type of liver cancer. We applied a machine learning approach with maximum-relevance-minimum-redundancy (mRMR) algorithm followed by in...