A comprehensive performance analysis of various Multiple Sequence Alignment tools

Team Members:

  • Arnav Aima - 99864675
  • Sakshi Dubey - 48131141
  • Suhani Mehta - 47986909

Abstract:

Multiple Sequence Alignment(MSA) is a biological concept of aligning three or more sequences. It is of great importance for studying the genetic functions, structures and evolution process of the biological sequences. The aligning of multiple sequences is one of the most fundamental problems in Bioinformatics and it has been widely used for a lot of biological applications like predicting the shapes of proteins, constructing the phylogeny trees, etc . MSAs demand extremely sensitive computational methodologies to come up with precise results. The objective of this project is to conduct a comparative study on various MSA tools on the basis of computation time, accuracy, memory use and sequence length to identify the best use-case for each.

Plan of Action:

Phase 1: Review relevant research work and develop understanding of MSA algorithms.

Phase 2: Use data fetched from PDB in FASTA format and derive strategies to conduct comparative study of different tools.

Phase3: Test the performance of MSA tools based on accuracy, speed, memory and sequence length.

Phase 4: Evaluate the results and prepare a detailed report on inferences.

Workload:

  • Arnav Aima: Responsible for testing T-Coffee MSA tool and evaluate results.
  • Sakshi Dubey: Responsible for testing MUSCLE MSA tool and evaluate results.
  • Suhani Mehta: Responsible for testing Kalign MSA tool and evaluate results.

*All team members would work towards understanding the research along with recording and comparing observations.