Publications (7)4.2 Total impact
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ABSTRACT: RNA sequences can form structures which are conserved throughout evolution and the question of aligning two RNA secondary structures has been extensively studied. Most of the previous alignment algorithms require the input of gap opening and gap extension penalty parameters. The choice of appropriate parameter values is controversial as there is little biological information to guide their assignment. In this paper, we present an algorithm which circumvents this problem. Instead of finding an optimal alignment with predefined gap opening penalty, the algorithm finds the optimal alignment with exact number of aligned blocks. 
Conference Paper: A Bayesian approach to pairwise RNA Secondary Structure Alignment
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ABSTRACT: In solving the question of alignment of two RNA secondary structures, it is not clear how to choose parameters for the introduction of gaps in the alignment. We introduce a Bayesian approach for aligning two RNA secondary structures. The algorithm can not only compute the optimal alignment itself but also some interesting posteriors such as posteriors of substitution matrix and gap opening penalties. The running time of this algorithm is O(p<sub>1</sub> p<sub>2 </sub>nm), where p<sub>1</sub> and p<sub>2</sub> are the number of base pairs in RNA structures A and B, and n and m are the lengths of the two RNA secondary structures respectively 
Article: Multiple RNA structure alignment
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ABSTRACT: RNA structures can be viewed as a kind of special strings with some characters bonded with each other. The question of aligning two RNA structures has been studied for a while, and there are several successful algorithms that are based upon different models. In this paper, by adopting the model introduced in [18], we propose two algorithms to attack the question of aligning multiple RNA structures. We reduce the multiple RNA structure alignment problem to the problem of aligning two RNA structure alignments. 
Conference Paper: Alignment between Two Multiple Alignments
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ABSTRACT: Alignment of two multiple alignments arises naturally when constructing approximate multiple sequence alignments progressively. In this paper, we consider the problem of alignment of two multiple alignments with SPscore and linear gap costs. When there is no gap opening cost, this problem can be solved using the wellknown dynamic programming algorithm for two sequences by viewing each column in the multiple alignments as an element. However if there are gap opening costs (sometimes referred as affine gap costs) then the problem becomes nontrivial. Gotoh [4] suggested a procedure for this problem and stated that “the total arithmetic operations used is close to (quadratic) in typical cases”. Kececioglu and Zhang [7] gave heuristic algorithms based on optimistic and pessimistic gap counts and conjectured that this problem is NPcomplete. In this paper we prove that this problem is indeed NPcomplete and therefore settle this open problem. We then propose another heuristic algorithm for this problem. 
Conference Paper: Pattern Matching and Local Alignment for RNA Structures
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ABSTRACT: The primary structure of a ribonucleic acid (RNA) molecule can be represented as a sequence of nucleotides (bases) over the alphabet {A, C, G, U}. The secondary or tertiary structure of an RNA is a set of base pairs which form bonds between AU and GC. For secondary structures, these bonds have been traditionally assumed to be onetoone and noncrossing. This paper considers pattern matching as well as local alignment between two RNA structures. For pattern matching, we present two algorithms, one for obtaining an exact match, the other for approximate match. We then present an algorithm for RNA local structural alignment. 
Conference Paper: Alignment between Two RNA Structures
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ABSTRACT: The primary structure of a ribonucleic acid (RNA) molecule can be represented as a sequence of nucleotides (bases) over the fourletter alphabet {A,C, G, U}. The RNA secondary and tertiary structures can be represented as a set of nested base pairs and a set of crossing base pairs, respectively. These base pairs form bonds between A–U,–C–G, and G–U. This paper considers alignment with affine gap penalty between two RNA molecule structures. In general this problem is Max SNPhard for tertiary structures. We present an algorithm for the case where aligned base pairs are noncrossing. Experimental results show that this algorithm can be used for practical application of RNA structure alignment. 
Conference Paper: Finding Common RNA Secondary Structures from RNA Sequences.
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ABSTRACT: RNAs (Ribonucleic Acids) play an important role when organisms reproduce themselves. RNAs are singlestranded, however they tend to form higher order structures such as secondary or tertiary structures by folding onto themselves. It is the RNA structures that determine the functions of RNA sequences. Since it is very difficult to crystallize and/or get nuclear magnetic resonance spectrum data for large RNA molecules, reliable methods to determine RNA structures from the primary sequences is important. An important step toward the deter mination of RNA structure is the prediction of RNA secondary structures. Based on a reliable RNA secondary structure, possible tertiary interactions that occur between secondary structural elements and between these elements and single stranded region can be characterized. Thermodynamic stability methods have been developed [5] to fold a single RNA into secondary structures with minimum or near minimum energy with some success. Phylogenetic comparative methods are more successful which try to determine the common secondary structures from a set of RNA sequences by checking a large number of possible base pair ings for their possible conservation. However this method is very tedious since it is basically performed manually. In this abstract, we propose an algorithm using dynamic programming trying to automate the phylogenetic comparative pro cess. Given three RNA sequences, we first apply the folding algorithms for each sequence to determine the frequently recurring stems which are considered to be thermodynamically favourable. We then apply our algorithm to the three stem lists generated from the folding algorithm to determine the common secondary structures.We have applied our method to three viruses: cocksackievirus, human rhinovirus (type 14), and poliovirus (type 3). Our method successfully produced the main components of the common secondary structures of these viruses.
Publication Stats
47  Citations  
4.20  Total Impact Points  
Top Journals
Institutions

20042007

University Health Network
 Division of Experimental Therapeutics
Toronto, Ontario, Canada


2003

The University of Western Ontario
 Department of Computer Science
London, Ontario, Canada
