| dc.description.abstract | In bioinformatics, proteins, large biological molecules consisting long chain of
amino acids, are described by a sequence of 20 amino acids. To analyze these
protein sequences pairwise alignment is being used, which identify regions of
similarity that may be a result of structural, functional and/or evolutionary relationship
between them. Traditional pairwise alignment algorithms work on
residue level; it does not account structural or functional information that protein
carries. A new approach for protein sequence analysis is being proposed
here, pairwise alignment of two protein sequences based on segments. Segments
of the sequences can be formed on the basis of protein feature, i.e., functional sites
or secondary structure of the protein. Each segment carries a type and weight for
the alignment process. Algorithm should align two sequences such that segments
with weight higher than threshold value must align with the similar type of segment
and score for the alignment must be maximal for given scoring function.
Here, we are proposing a generic framework to understand, explore and experiment
proteins based on their features, i.e. structure, function, and evolution. | |
