Dot matrices and genetics algorithms for MSA

Multiple Sequence Alignment (MSA) is among the best important tasks in computational biology. Genetic Algorithms are stochastic approaches for efficient and robust search. With the increasing rate of determination of sequences, the emphasis in biological sequence comparison has turned to the simultaneous alignment of several sequences. The consistency of align able sequence fragments for a set of sequences can be implemented by using dot matrices. A set of algorithms has been developed (a) to discover the consistency and have MSA using dot matrices (CDM), (b) to construct the MSA algorithm (CSAA) based on an extension of CDM,(c) to create a MSA algorithm based on the divide and conquer method and the use of a Genetic Algorithm (DCGA). CDM with its internal phase can minimize the number of pair wise comparisons in MSA giving better performance. CDM is also efficient in finding conserved motifs (short sequence segments that are important in protein structure) among very distantly related sequences and using also CSAA that can be used for the MSA. Finally, the DCGA framework that contains CDM or CSAA and Genetic Algorithm (GA) provides better performance than the GA. Simulation experiments are produced.