Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 2 of 2
Full-Text Articles in Engineering
Accelerated Non-Coding Rna Searches With Covariance Model Approximations, Jennifer A. Smith
Accelerated Non-Coding Rna Searches With Covariance Model Approximations, Jennifer A. Smith
Jennifer A. Smith
Covariance models (CMs) are a very sensitive tool for finding non-coding RNA (ncRNA) genes in DNA sequence data. However, CMs are extremely slow. One reason why CMs are so slow is that they allow all possible combinations of insertions and deletions relative to the consensus model even though the vast majority of these are never seen in practice. In this paper we examine reduction in the number of states in covariance models. A simplified CM with reduced states which can be scored much faster is introduced. A comparison of the results of a full CM versus a reduced-state model found …
A Genetic Algorithms Approach To Non-Coding Rna Gene Searches, Jennifer A. Smith
A Genetic Algorithms Approach To Non-Coding Rna Gene Searches, Jennifer A. Smith
Jennifer A. Smith
A genetic algorithm is proposed as an alternative to the traditional linear programming method for scoring covariance models in non-coding RNA (ncRNA) gene searches. The standard method is guaranteed to find the best score, but it is too slow for general use. The observation that most of the search space investigated by the linear programming method does not even remotely resemble any observed sequence in real sequence data can be used to motivate the use of genetic algorithms (GAs) to quickly reject regions of the search space. A search space with many local minima makes gradient decent an unattractive alternative. …