Bi-objective integer programming for RNA secondary structure prediction with pseudoknots
نویسندگان
چکیده
منابع مشابه
Dynamic programming algorithms for RNA secondary structure prediction with pseudoknots
This paper shows simple dynamic programming algorithms for RNA secondary structure prediction with pseudoknots. For a basic version of the problem (i.e., maximizing the number of base pairs), this paper presents an O(n) time exact algorithm and an O(n4− ) time approximation algorithm. The latter one outputs, for most RNA sequences, a secondary structure in which the number of base pairs is at l...
متن کاملRNA Secondary Structure Prediction with Simple Pseudoknots
Pseudoknots are widely occurring structural motifs in RNA. Pseudoknots have been shown to be functionally important in different RNAs which play regulatory, catalytic, or structural roles in cells. Current biophysical methods to identify the presence of pseudoknots are extremely time consuming and expensive. Therefore, bioinformatics approaches to accurately predict such structures are highly d...
متن کاملDP Algorithms for RNA Secondary Structure Prediction with Pseudoknots
This paper describes simple DP (dynamic programming) algorithms for RNA secondary structure prediction with pseudoknots, for which no explicit DP algorithm had been known. Results of preliminary computational experiments are described too.
متن کاملIPknot: fast and accurate prediction of RNA secondary structures with pseudoknots using integer programming
MOTIVATION Pseudoknots found in secondary structures of a number of functional RNAs play various roles in biological processes. Recent methods for predicting RNA secondary structures cover certain classes of pseudoknotted structures, but only a few of them achieve satisfying predictions in terms of both speed and accuracy. RESULTS We propose IPknot, a novel computational method for predicting...
متن کاملA dynamic programming algorithm for RNA structure prediction including pseudoknots.
We describe a dynamic programming algorithm for predicting optimal RNA secondary structure, including pseudoknots. The algorithm has a worst case complexity of O(N6) in time and O(N4) in storage. The description of the algorithm is complex, which led us to adopt a useful graphical representation (Feynman diagrams) borrowed from quantum field theory. We present an implementation of the algorithm...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: BMC Bioinformatics
سال: 2018
ISSN: 1471-2105
DOI: 10.1186/s12859-018-2007-7