Efficient algorithms for locating the length-constrained heaviest segments with applications to biomolecular sequence analysis

Authors: Lin Y-L.1; Jiang T.2; Chao K-M.3

Source: Journal of Computer and System Sciences, Volume 65, Number 3, November 2002 , pp. 570-586(17)

Publisher: Academic Press

Key:
Free Content - Free Content
New Content - New Content
Subscribed Content - Subscribed Content
Free Trial Content - Free Trial Content

Abstract:

We study two fundamental problems concerning the search for interesting regions in sequences: (i) given a sequence of real numbers of length n and an upper boundU, find a consecutive subsequence of length at most U with the maximum sum and (ii) given a sequence of real numbers of length n and a lower bound L, find a consecutive subsequence of length at least L with the maximum average. We present an O(n)-time algorithm for the first problem and an O(n log L)-time algorithm for the second. The algorithms have potential applications in several areas of biomolecular sequence analysis including locating GC-rich regions in a genomic DNA sequence, post-processing sequence alignments, annotating multiple sequence alignments, and computing length-constrained ungapped local alignment. Our preliminary tests on both simulated and real data demonstrate that the algorithms are very efficient and able to locate useful (such as GC-rich) regions.

Language: English

Document Type: Research article

DOI: 10.1016/S0022-0000(02)00010-7

Affiliations: 1: Department of Computer Science and Information Management, Providence University, 200 Chung Chi Road, Shalu, Taichung County, 433 Taiwan 2: Department of Computer Science, University of California Riverside, Riverside, CA 92521-0144, USA 3: Department of Life Science, National Yang-Ming University, Taipei, 112 Taiwan

The full text electronic article is available for purchase. You will be able to download the full text electronic article after payment.

$54.13 plus tax      Refund Policy

 

OR

Back to top

Key:
Free Content - Free Content
New Content - New Content
Subscribed Content - Subscribed Content
Free Trial Content - Free Trial Content
Share this item with others: These icons link to social bookmarking sites where readers can share and discover new web pages.
Page Help Click here for Page Help
Shopping cart
Tools
Sign in






Need to register?
Sign up here
Text size: A | A | A | A