Prediction of Consensus RNA Secondary Structures Including Pseudoknots
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
A leader-based parallel cross entropy algorithm for MCP
Proceedings of the 9th annual conference companion on Genetic and evolutionary computation
Finding a Common Motif of RNA Sequences Using Genetic Programming: The GeRNAMo System
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Approximating the maximum vertex/edge weighted clique using local search
Journal of Heuristics
Reactive and dynamic local search for max-clique: Engineering effective building blocks
Computers and Operations Research
Dynamic local search for the maximum clique problem
Journal of Artificial Intelligence Research
A Max-SAT inference-based pre-processing for Max-clique
SAT'08 Proceedings of the 11th international conference on Theory and applications of satisfiability testing
Scalable Uniform Graph Sampling by Local Computation
SIAM Journal on Scientific Computing
Cooperating local search for the maximum clique problem
Journal of Heuristics
Local search with edge weighting and configuration checking heuristics for minimum vertex cover
Artificial Intelligence
A scalable eigensolver for large scale-free graphs using 2D graph partitioning
Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis
Rapid ab initio RNA folding including pseudoknots via graph tree decomposition
WABI'06 Proceedings of the 6th international conference on Algorithms in Bioinformatics
Consensus folding of unaligned RNA sequences revisited
RECOMB'05 Proceedings of the 9th Annual international conference on Research in Computational Molecular Biology
RNA secondary structure prediction via energy density minimization
RECOMB'06 Proceedings of the 10th annual international conference on Research in Computational Molecular Biology
A study of accessible motifs and RNA folding complexity
RECOMB'06 Proceedings of the 10th annual international conference on Research in Computational Molecular Biology
Maximum regular induced subgraphs in 2P3-free graphs
Theoretical Computer Science
Subgraph extraction and metaheuristics for the maximum clique problem
Journal of Heuristics
Constructing structural alignment of RNA sequences by detecting and assessing conserved stems
LSMS'07 Proceedings of the 2007 international conference on Life System Modeling and Simulation
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Motivation: RNA structure motifs contained in mRNAs have been found to play important roles in regulating gene expression. However, identification of novel RNA regulatory motifs using computational methods has not been widely explored. Effective tools for predicting novel RNA regulatory motifs based on genomic sequences are needed. Results: We present a new method for predicting common RNA secondary structure motifs in a set of functionally or evolutionarily related RNA sequences. This method is based on comparison of stems (palindromic helices) between sequences and is implemented by applying graph-theoretical approaches. It first finds all possible stable stems in each sequence and compares stems pairwise between sequences by some defined features to find stems conserved across any two sequences. Then by applying a maximum clique finding algorithm, it finds all significant stems conserved across at least k sequences. Finally, it assembles in topological order all possible compatible conserved stems shared by at least k sequences and reports a number of the best assembled stem sets as the best candidate common structure motifs. This method does not require prior structural alignment of the sequences and is able to detect pseudoknot structures. We have tested this approach on some RNA sequences with known secondary structures, in which it is capable of detecting the real structures completely or partially correctly and outperforms other existing programs for similar purposes. Availability: The algorithm has been implemented in C++ in a program called comRNA, which is available at http://ural.wustl.edu/softwares.html