Xingran Xue

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Given the importance of non-coding RNAs to cellular regulatory functions and rapid growth of RNA transcripts, computational prediction of RNA ter-tiary structure remains highly demanded yet significantly challenging. Even for a short RNA sequence, the space of tertiary conformations is immense; existing methods to identify native-like conformations mostly(More)
Stochastic context-free grammar (SCFG) has been successful in modeling biomolecular structures, typically RNA secondary structure, for statistical analysis and structure prediction. Context-free grammar rules specify parallel and nested co-occurrences of terminals, and thus are ideal for modeling nucleotide canonical base pairs that constitute the RNA(More)
MOTIVATION Given the importance of non-coding RNAs to cellular regulatory functions, it would be highly desirable to have accurate computational prediction of RNA 3D structure, a task which remains challenging. Even for a short RNA sequence, the space of tertiary conformations is immense; existing methods to identify native-like conformations mostly resort(More)
We prove that, for many parameterized problems in the class FPT, the existence of polynomial kernels implies the collapse of the W-hierarchy (i.e., W[P] = FPT). The collapsing results are also extended to assumed exponential kernels for problems in the class FPT. In particular , we establish a close relationship between polynomial (and exponential)(More)
UNLABELLED TRFolder-W is a web server capable of predicting core structures of telomerase RNA (TR) in yeast genomes. TRFolder is a command-line Python toolkit for TR-specific structure prediction. We developed a web-version built on the django web framework, leveraging the work done previously, to include enhancements to increase flexibility of usage. To(More)
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