Recently, the detection of previously unknown, frequently occurring pattern is regarded as a difficult problem. We call this pattern as “motif”. Many researchers have proposed algorithms for discovering the motif. However, if the optimal period length of the motif is not known in advance, we can not use their algorithms for discovering the motif. In this paper, we attempt to determine the optim...

Computer Science) Protein-DNA Binding: Discovering Motifs and Distinguishing Direct From Indirect Interactions by Raluca M. Gordân Department of Computer Science Duke University Date: Approved: Alexander J. Hartemink, Advisor Uwe Ohler Bruce R. Donald David M. MacAlpine An abstract of a dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in t...

The computational discovery of DNA motifs is one of the most important problems in molecular biology and computational biology, and it has not yet been resolved in an efficient manner. With previous research, we have solved the single-objective motif discovery problem (MDP) based on biogeography-based optimization (BBO) and gained excellent results. In this study, we apply multi-objective bioge...

A new category of protein motif is introduced. This type of motif captures, in addition to global structure, the nested structure of its component parts. A dataset of four proteins is represented using this scheme. A structured machine discovery procedure is used to discover recurrent amino acid motifs and this knowledge is utilized for the expression of subsequent protein motif discoveries. Ex...

Many computational approaches have been introduced for the problem of motif identification in a set of biological sequences, which are classified according to the type of motifs discovered. In this study, we propose a model to discover motif in large set of unaligned sequences in considerably minimum time using genetic algorithm based probabilokistic Motif discovery model. The proposed algorith...

We study a natural probabilistic model for motif discovery that has been used to experimentally test the quality of motif discovery programs. In this model, there are k background sequences, and each character in a background sequence is a random character from an alphabet Σ. A motif G = g1g2 · · · gm is a string of m characters. Each background sequence is implanted into a probabilistically ge...

Multiple Sequence Alignment and Motif Discovery, known as NP-hard problems, are two fundamental tasks in Bioinformatics. Existing approaches to these two problems are based on either local search methods such as Expectation Maximization (EM), Gibbs Sampling or greedy heuristic methods. In this work, we develop a convex relaxation approach to both problems based on the recent concept of atomic n...

Transcription factor (TF) binding site discovery is an important step in understanding transcriptional regulation. Many computational tools have already been developed, but their success in detecting TF motifs is still limited. We believe one of the main reasons for the low accuracy of current methods is that they do not take into account the structural aspects of TF-DNA interaction. We have pr...