MOTIVATION: Evaluating all possible internal loops is one of the key steps in predicting the optimal secondary structure of an RNA molecule. The best algorithm available runs in time O(L(3)), L is the length of the RNA. RESULTS: We propose a new algorithm for evaluating internal loops, its run-time is O(M(*)log(2)L), M < L(2) is a number of possible nucleotide pairings. We created a software tool Afold which predicts the optimal secondary structure of RNA molecules of lengths up to 28 000 nt, using a computer with 2 Gb RAM. We also propose algorithms constructing sets of conditionally optimal multi-branch loop free (MLF) structures, e.g. the set that for every possible pairing (x, y) contains an optimal MLF structure in which nucleotides x and y form a pair. All the algorithms have run-time O(M(*)log(2)L).
MOTIVATION: Evaluating all possible internal loops is one of the key steps in predicting the optimal secondary structure of an RNA molecule. The best algorithm available runs in time O(L(3)), L is the length of the RNA. RESULTS: We propose a new algorithm for evaluating internal loops, its run-time is O(M(*)log(2)L), M < L(2) is a number of possible nucleotide pairings. We created a software tool Afold which predicts the optimal secondary structure of RNA molecules of lengths up to 28 000 nt, using a computer with 2 Gb RAM. We also propose algorithms constructing sets of conditionally optimal multi-branch loop free (MLF) structures, e.g. the set that for every possible pairing (x, y) contains an optimal MLF structure in which nucleotides x and y form a pair. All the algorithms have run-time O(M(*)log(2)L).
Authors: Olga V Matveeva; Yury D Nechipurenko; Evgeniy Riabenko; Chikako Ragan; Nafisa N Nazipova; Aleksey Y Ogurtsov; Svetlana A Shabalina Journal: Bioinformatics Date: 2016-09-01 Impact factor: 6.937
Authors: M F Jones; X Ling Li; M Subramanian; Svetlana A Shabalina; T Hara; Y Zhu; J Huang; Y Yang; L M Wakefield; K V Prasanth; A Lal Journal: Cell Death Differ Date: 2015-02-20 Impact factor: 15.828
Authors: Olga V Matveeva; Yibin Kang; Alexey N Spiridonov; Pål Saetrom; Vladimir A Nemtsov; Aleksey Y Ogurtsov; Yury D Nechipurenko; Svetlana A Shabalina Journal: PLoS One Date: 2010-04-20 Impact factor: 3.240
Authors: Elizabeth M Fozo; Kira S Makarova; Svetlana A Shabalina; Natalya Yutin; Eugene V Koonin; Gisela Storz Journal: Nucleic Acids Res Date: 2010-02-15 Impact factor: 16.971
Authors: Douglas Tsao; Svetlana A Shabalina; Josée Gauthier; Nikolay V Dokholyan; Luda Diatchenko Journal: Nucleic Acids Res Date: 2011-04-12 Impact factor: 16.971
Authors: David Managadze; Igor B Rogozin; Diana Chernikova; Svetlana A Shabalina; Eugene V Koonin Journal: Genome Biol Evol Date: 2011-11-09 Impact factor: 3.416
Authors: Andrea G Nackley; Svetlana A Shabalina; Jason E Lambert; Mathew S Conrad; Dustin G Gibson; Alexey N Spiridonov; Sarah K Satterfield; Luda Diatchenko Journal: PLoS One Date: 2009-04-13 Impact factor: 3.240