Faster algorithms for RNA-folding using the Four-Russians method

Venkatachalam, Balaji; Gusfield, Dan; Frid, Yelena

doi:10.1186/1748-7188-9-5

Cited by 18 publications

(16 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A fast tag correcting algorithm could also be used in an integrated development environment to provide feedback to the user about structural problems in the document being created. The Dyck language arises naturally in many biological applications like RNA folding [14]. Table 1 summarizes previous results and our results on computing distance to Dyck(k).…”

Section: Introductionmentioning

confidence: 84%

Fast Algorithms for Parsing Sequences of Parentheses with Few Errors

Bačkurs

Onak

2016

Proceedings of the 35th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems

View full text Add to dashboard Cite

We consider the problem of fixing sequences of unbalanced parentheses. A classic algorithm based on dynamic programming computes the optimum sequence of edits required to solve the problem in cubic time. We show the first algorithm that runs in linear time when the number of necessary edits is small. More precisely, our algorithm runs in O(n) + d O(1) time, where n is the length of the sequence to be fixed and d is the minimum number of edits.The problem of fixing parentheses sequences is related to the task of repairing semi-structured documents such as XML and JSON.

show abstract

Section: Introductionmentioning

confidence: 84%

Fast Algorithms for Parsing Sequences of Parentheses with Few Errors

Bačkurs

Onak

2016

Proceedings of the 35th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems

View full text Add to dashboard Cite

show abstract

“…We only discuss the experimental results on a desktop and two GPU cards in this paper. Detailed notes on running times can be found in [26].…”

Section: Resultsmentioning

confidence: 99%

“…Due to space limitations, this manuscript focuses mostly on the theoretical aspects and describes the experimental results briefly. Detailed discussion can be found in [26].…”

Section: Introductionmentioning

confidence: 99%

Faster Algorithms for RNA-Folding Using the Four-Russians Method

Venkatachalam

Gusfield

Frid

2013

Lecture Notes in Computer Science

Self Cite

View full text Add to dashboard Cite

Background:The secondary structure that maximizes the number of non-crossing matchings between complimentary bases of an RNA sequence of length n can be computed in O(n 3 ) time using Nussinov's dynamic programming algorithm. The Four-Russians method is a technique that reduces the running time for certain dynamic programming algorithms by a multiplicative factor after a preprocessing step where solutions to all smaller subproblems of a fixed size are exhaustively enumerated and solved. Frid and Gusfield designed an O( n 3 log n ) algorithm for RNA folding using the Four-Russians technique. In their algorithm the preprocessing is interleaved with the algorithm computation. Theoretical results: We simplify the algorithm and the analysis by doing the preprocessing once prior to the algorithm computation. We call this the two-vector method. We also show variants where instead of exhaustive preprocessing, we only solve the subproblems encountered in the main algorithm once and memoize the results. We give a simple proof of correctness and explore the practical advantages over the earlier method. The Nussinov algorithm admits an O(n 2 ) time parallel algorithm. We show a parallel algorithm using the two-vector idea that improves the time bound to O( n 2 log n ). Practical results: We have implemented the parallel algorithm on graphics processing units using the CUDA platform. We discuss the organization of the data structures to exploit coalesced memory access for fast running times. The ideas to organize the data structures also help in improving the running time of the serial algorithms. For sequences of length up to 6000 bases the parallel algorithm takes only about 2.5 seconds and the two-vector serial method takes about 57 seconds on a desktop and 15 seconds on a server. Among the serial algorithms, the two-vector and memoized versions are faster than the Frid-Gusfield algorithm by a factor of 3, and are faster than Nussinov by up to a factor of 20. The source-code for the algorithms is available at http://github.com/ ijalabv/FourRussiansRNAFolding.

show abstract

“…There are other algorithmic efforts to speed up RNA folding, including an O(n3/ log n) algorithm using the Four-Russians method (Venkatachalam et al , 2014), and two other sub-cubic algorithms inspired by fast matrix multiplication and context-free parsing (Bringmann et al , 2016; Zakov et al , 2011). We note that all of them are based on the classical cubic-time bottom-up algorithm, and thus orthogonal to our left-to-right approach.…”

Section: Discussionmentioning

confidence: 99%

LinearFold: linear-time approximate RNA folding by 5'-to-3' dynamic programming and beam search

Zhang²,

et al. 2019

View full text Add to dashboard Cite

Motivation Predicting the secondary structure of an ribonucleic acid (RNA) sequence is useful in many applications. Existing algorithms [based on dynamic programming] suffer from a major limitation: their runtimes scale cubically with the RNA length, and this slowness limits their use in genome-wide applications. Results We present a novel alternative O(n3)-time dynamic programming algorithm for RNA folding that is amenable to heuristics that make it run in O(n) time and O(n) space, while producing a high-quality approximation to the optimal solution. Inspired by incremental parsing for context-free grammars in computational linguistics, our alternative dynamic programming algorithm scans the sequence in a left-to-right (5′-to-3′) direction rather than in a bottom-up fashion, which allows us to employ the effective beam pruning heuristic. Our work, though inexact, is the first RNA folding algorithm to achieve linear runtime (and linear space) without imposing constraints on the output structure. Surprisingly, our approximate search results in even higher overall accuracy on a diverse database of sequences with known structures. More interestingly, it leads to significantly more accurate predictions on the longest sequence families in that database (16S and 23S Ribosomal RNAs), as well as improved accuracies for long-range base pairs (500+ nucleotides apart), both of which are well known to be challenging for the current models. Availability and implementation Our source code is available at https://github.com/LinearFold/LinearFold, and our webserver is at http://linearfold.org (sequence limit: 100 000nt). Supplementary information Supplementary data are available at Bioinformatics online.

show abstract

Faster algorithms for RNA-folding using the Four-Russians method

Cited by 18 publications

References 32 publications

Fast Algorithms for Parsing Sequences of Parentheses with Few Errors

Fast Algorithms for Parsing Sequences of Parentheses with Few Errors

Faster Algorithms for RNA-Folding Using the Four-Russians Method

LinearFold: linear-time approximate RNA folding by 5'-to-3' dynamic programming and beam search

Contact Info

Product

Resources

About