1st Student's Major

Computer Information Science

1st Student's College

Science, Engineering and Technology

Students' Professional Biography

Tejas Gandhi is a computer science senior at Minnesota State University, Mankato.

Mentor's Name

Christophe Veltsos

Mentor's Email Address


Mentor's Department

Computer Information Science

Mentor's College

Science, Engineering and Technology

Other Mentors

Timothy Secott


The fact that biological sequences can be represented as strings belonging to a finite alphabet (A, C, G, and T for DNA) plays an important role in connecting biology to computer science. String representation allows researchers to apply various string comparison techniques available in computer science. As a result, various applications have been developed that facilitate the task of sequence alignment. The problem of finding sequence alignments consists of finding the best match between two biological sequences. A best match can infer an evolutionary relationship and functional similarity. However, there is a lack of research on how reliable and efficient these applications are especially when it comes to comparing two sequences that might not be highly similar (but could have common patterns that are small yet biologically significant). This study compares two biological sequence comparison packages, namely WuBlast2 and Fasta3, which implement Blast and FastA algorithms, respectively. In order to do so, a framework was developed to facilitate the task of data collection and create meaningful reports. Amino acid sequences corresponding to related proteins, as well as the DNA sequences encoding these proteins, were analyzed with matching parameters for each application. Observations showed a trend of increasing variations between the matches produced by the two applications with decreasing sequence similarity.

Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License



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