Efficient algorithms for molecular sequence analysis.

Efficient Algorithms for Sequence Analysis∗

We consider new algorithms for the solution of many dynamic programming recurrences for sequence comparison and for RNA secondary structure prediction. The techniques upon which the algorithms are based effectively exploit the physical constraints of the problem to derive more efficient methods for sequence analysis.

Efficient Algorithms for Sequence Segmentation

The sequence segmentation problem asks for a partition of the sequence into k non-overlapping segments that cover all data points such that each segment is as homogeneous as possible. This problem can be solved optimally using dynamic programming in O(nk) time, where n is the length of the sequence. Given that sequences in practice are too long, a quadratic algorithm is not an adequately fast s...

Efficient Algorithms for Range Queries in Protein Sequence Analysis

Efficient sequence alignment algorithms.

Sequence alignments are becoming more important with the increase of nucleic acid data. Fitch and Smith have recently given an example where multiple insertion/deletions (rather than a series of adjacent single insertion/deletions) are necessary to achieve the correct alignment. Multiple insertion/deletions are known to increase computation time from O(n2) to O(n3) although Gotoh has presented ...

Efficient combinatorial algorithms for DNA sequence processing

The modern era of molecular biology began with the discovery of the double helical structure of DNA. Today, sequencing nucleic acids, the determination of genetic information at the most fundamental level, is a major tool of biological research [44]. This revolution in biology has created a huge amount of data at great speed by directly reading DNA sequences. The growth rate of data volume is e...