Single nucleotide variants (SNVs) contribute to human genomic diversity. Synonymous
SNVs are previously considered to be “silent,” but mounting evidence has revealed that …

Long non-coding RNAs (lncRNAs) are a rapidly expanding field of research, with many new
transcripts identified each year. However, only a small subset of lncRNAs has been …

Motivation The secondary structure of RNA is of importance to its function. Over the last few
years, several papers attempted to use machine learning to improve de novo RNA …

There is increasing interest in the roles of covalently modified nucleotides in RNA. There has
been, however, an inability to account for modifications in secondary structure prediction …

While predicting the secondary structure of RNA is vital for researching its function,
determining RNA secondary structure is challenging, especially for that with pseudoknots …

Despite the popularity of computer-aided study and design of RNA molecules, little is known
about the accuracy of commonly used structure modeling packages in tasks sensitive to …

An RNA design algorithm takes a target RNA structure and finds a sequence that folds into
that structure. This is fundamentally important for engineering therapeutics using RNA …

Deep learning methods for RNA secondary structure prediction have shown higher
performance than traditional methods, but there is still much room to improve. It is known that …

Noncoding RNAs play important roles in cell and their secondary structures are vital for
understanding their tertiary structures and functions. Many prediction methods of RNA …

Background RNA features a highly negatively charged phosphate backbone that attracts a
cloud of counter-ions that reduce the electrostatic repulsion in a concentration dependent …