Performance Evaluation of Structured and Semi-Structured Bioinformatics Tools: A Comparative Study

TL;DR

This study compares the performance of structured and semi-structured bioinformatics tools in accessing biological databases via web interfaces, highlighting their respective strengths and weaknesses.

Contribution

It provides a comparative evaluation of structured and semi-structured data retrieval methods in bioinformatics, emphasizing the viability of semi-structured tools as alternatives.

Findings

Semi-structured tools are a viable alternative to structured tools.

Each method has inherent advantages and disadvantages.

Performance varies depending on query complexity.

Abstract

There is a wide range of available biological databases developed by bioinformatics experts, employing different methods to extract biological data. In this paper, we investigate and evaluate the performance of some of these methods in terms of their ability to efficiently access bioinformatics databases using web-based interfaces. These methods retrieve bioinformatics information using structured and semi-structured data tools, which are able to retrieve data from remote database servers. This study distinguishes each of these approaches and contrasts these tools. We used Sequence Retrieval System (SRS) and Entrez search tools for structured data, while Perl and BioPerl search programs were used for semi-structured data to retrieve complex queries including a combination of text and numeric information. The study concludes that the use of semi-structured data tools for accessing bioinformatics databases is a viable alternative to the structured tools, though each method is shown to have certain inherent advantages and disadvantages.