Multiple sequence alignment for phylogenetic tree construction

ABSTRACT The bioinformatics research has accumulated a large amount of data. The cost of storing is decreasing as the hardware technology is advancing. Since more and more data is added in the field of proteomics, there is a great need for computational methods to be really efficient. The biological data has significant complexity due to the presence of data in different formats and to derive knowledge from these complex databases is the key problem of this era. Machine learning and data mining techniques are required which can scale to the size of the problems and can be made to suit and hence applied to biology. To a molecule, the part of molecular sequence is functionally very important and which is resistant to change. So comparative approaches are used in order to ensure the reliability of sequence alignment. The problem of multiple sequence alignment is a part of evolutionary history. The different pairwise methods are described in this present work. For each individual sequence position, an explicit homologous correspondence is established, aligning species column wise. A method is introduced for aligning sequences based on local alignment with consensus sequence. Medicago Sativa varities are loaded from NCBI databank and phylogenetic trees are constructed for divided parts of dataset.