• Dr Neeta Maitre

Multiple sequence alignment is an important step in gene prediction. The sequences involved in the alignment process are assumed to be derived from a single ancestral sequence i.e. homologous. These sequences are subjected to sequence algorithms for the homology search. The results obtained by sequence alignment can be used for locating genes by identifying exon positions or can be utilized to interpret evolutionary origin. The time complexity of the algorithms governs the runtime, which in turn drives the greenhouse gas (GHG) emissions. GHG emissions are critical from a global sustainability point of view. In this work, a method to compare the relative standing of algorithms from GHG emissions point of view is developed. T-Coffee and MAFFT algorithms are used as examples. The peculiar feature of these algorithms is that both are progressive in nature and can cover all sized sequences used for alignment. MAFFT is observed to have relatively lower GHG emissions as compared to T-Coffee.

Sustainability, Multiple sequence alignment algorithms, MAFFT, T-Coffee, GHG (Greenhouse Gases)

"Relative Greenhouse Gases Emissions of MSA Algorithms: A comparison of T-Coffee and MAFFT", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 7, page no.g247-g250, July-2021, Available :http://www.jetir.org/papers/JETIR2107765.pdf

"Relative Greenhouse Gases Emissions of MSA Algorithms: A comparison of T-Coffee and MAFFT", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 7, page no. ppg247-g250, July-2021, Available at : http://www.jetir.org/papers/JETIR2107765.pdf