Current Computational Models for Prediction of the Varied Interactions Related to Noncoding RNAs
1China University of Mining and Technology, Xuzhou, China
2Wake Forest University, Winston-Salem, USA
3Houston Methodist Research Institute, Houston, USA
Current Computational Models for Prediction of the Varied Interactions Related to Noncoding RNAs
Description
In recent years, an increasing number of experimental studies have shown that plenty of noncoding RNAs (ncRNAs) do not constitute transcriptional noise but play important roles in critical biological processes such as transcriptional and posttranscriptional regulation, epigenetic regulation, organ or tissue development, cell differentiation, cell cycle control, cellular transport, metabolic processes, and chromosome dynamics. Considering the important roles of ncRNAs in various biological processes, it is of no surprise that mutations and dysregulations of ncRNAs have been linked to the development and progression of a broad range of complex human diseases, such as breast cancer, hepatocellular cancer, prostate cancer, colon cancer, bladder cancer, thyroid cancer, lung cancer, ovarian cancer, leukemia, Alzheimer’s disease, diabetes, and HIV. The development of computational models to predict the various ncRNA-related interactions benefits the inference of ncRNA function, the identification of how ncRNA’s are associated to disease, ncRNA biomarker detection, and the potential design of drug targets.
We invite investigators to contribute reviews and original papers describing recent findings in the field of computational models for prediction of the varied interactions related to noncoding RNAs, such as ncRNA-disease association prediction, ncRNA functional similarity network construction, ncRNA function prediction, and miRNA-target interactions prediction.
Potential topics include, but are not limited to:
- ncRNA-disease association prediction
- ncRNA functional similarity network construction
- ncRNA function prediction
- miRNA-target interaction prediction
- Disease-related ncRNA-environmental factor interaction prediction
- miRNA-transcriptional factor interaction prediction
- ncRNA biomarker detection
- ncRNA and drug design
- ncRNA and PPI