TY - JOUR

T1 - A faster algorithm for simultaneous alignment and folding of RNA

AU - Ziv-Ukelson, Michal

AU - Gat-Viks, Irit

AU - Wexler, Ydo

AU - Shamir, Ron

PY - 2010/8/1

Y1 - 2010/8/1

N2 - The current pairwise RNA (secondary) structural alignment algorithms are based on Sankoff's dynamic programming algorithm from 1985. Sankoff's algorithm requires O(N6) time and O(N4) space, where N denotes the length of the compared sequences, and thus its applicability is very limited. The current literature offers many heuristics for speeding up Sankoff's alignment process, some making restrictive assumptions on the length or the shape of the RNA substructures. We show how to speed up Sankoff's algorithm in practice via non-heuristic methods, without compromising optimality. Our analysis shows that the expected time complexity of the new algorithm is O(N4ς(N)), where ς(N) converges to O(N), assuming a standard polymer folding model which was supported by experimental analysis. Hence, our algorithm speeds up Sankoff's algorithm by a linear factor on average. In simulations, our algorithm speeds up computation by a factor of 3-12 for sequences of length 25-250. Code and data sets are available, upon request.

AB - The current pairwise RNA (secondary) structural alignment algorithms are based on Sankoff's dynamic programming algorithm from 1985. Sankoff's algorithm requires O(N6) time and O(N4) space, where N denotes the length of the compared sequences, and thus its applicability is very limited. The current literature offers many heuristics for speeding up Sankoff's alignment process, some making restrictive assumptions on the length or the shape of the RNA substructures. We show how to speed up Sankoff's algorithm in practice via non-heuristic methods, without compromising optimality. Our analysis shows that the expected time complexity of the new algorithm is O(N4ς(N)), where ς(N) converges to O(N), assuming a standard polymer folding model which was supported by experimental analysis. Hence, our algorithm speeds up Sankoff's algorithm by a linear factor on average. In simulations, our algorithm speeds up computation by a factor of 3-12 for sequences of length 25-250. Code and data sets are available, upon request.

KW - Algorithms

KW - RNA

KW - computational molecular biology

KW - secondary structure

KW - sequence analysis

UR - http://www.scopus.com/inward/record.url?scp=77956077195&partnerID=8YFLogxK

U2 - 10.1089/cmb.2009.0197

DO - 10.1089/cmb.2009.0197

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AN - SCOPUS:77956077195

VL - 17

SP - 1051

EP - 1065

JO - Journal of Computational Biology

JF - Journal of Computational Biology

SN - 1066-5277

IS - 8

ER -