A Computational Bioinformatics Approach for Analysis of DNA and Protein Sequences Using Biopython

Abstract

The rapid development of genomic technologies has resulted in the generation of large amounts of biological sequence data. Efficient analysis and interpretation of this information require computational approaches that combine biology, computer science, and data analysis. Bioinformatics provides powerful methods for studying DNA, RNA, and protein sequences through computational pipelines. This research presents the development of a Python-based DNA sequence analysis pipeline using Biopython. The project was implemented using Visual Studio Code as the development environment. The pipeline performs fundamental sequence-analysis operations including FASTA parsing, sequence processing, GC content calculation, reverse complement generation, DNA transcription, and translation into protein sequences. The project demonstrates how programming-based approaches can automate basic molecular biology workflows and provide a foundation for more advanced applications in genomics, disease research, pharmaceutical research, and computational biology. Keywords: Bioinformatics, Biopython, Python, DNA Sequence Analysis, Computational Biology, Biotechnology, Genomics