AIMC Topic: RNA

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Using neural networks for reducing the dimensions of single-cell RNA-Seq data.

Nucleic acids research
While only recently developed, the ability to profile expression data in single cells (scRNA-Seq) has already led to several important studies and findings. However, this technology has also raised several new computational challenges. These include ...

RBPPred: predicting RNA-binding proteins from sequence using SVM.

Bioinformatics (Oxford, England)
MOTIVATION: Detection of RNA-binding proteins (RBPs) is essential since the RNA-binding proteins play critical roles in post-transcriptional regulation and have diverse roles in various biological processes. Moreover, identifying RBPs by computationa...

Primer on the Gene Ontology.

Methods in molecular biology (Clifton, N.J.)
The Gene Ontology (GO) project is the largest resource for cataloguing gene function. The combination of solid conceptual underpinnings and a practical set of features have made the GO a widely adopted resource in the research community and an essent...

The Gene Ontology and the Meaning of Biological Function.

Methods in molecular biology (Clifton, N.J.)
The Gene Ontology (GO) provides a framework and set of concepts for describing the functions of gene products from all organisms. It is specifically designed for supporting the computational representation of biological systems. A GO annotation is an...

Identifying RNA 5-methylcytosine sites via pseudo nucleotide compositions.

Molecular bioSystems
RNA 5-methylcytosine (mC) plays an important role in numerous biological processes. Accurate identification of the mC site is helpful for a better understanding of its biological functions. However, the drawbacks of the experimental methods available...