Stem Intiative

Tracking High-Performance Biosequence Clustering Jobs Using Common Web Interfaces

Student(s):  Franshetta Hibbler, Mississippi Valley State University


 

Contemporary methods have followed for the study of complex bacterial populations, such as 16S rRNA, directly from environmental or clinical samples. Alignment of data sets of 100,000+ sequences is necessary to identify potential gene clusters and families. Consequently, there is a demand for accurate and effective software systems and algorithms to conduct analysis. The goal of this research was to create a simple, efficient webpage that tracked computational jobs on several platforms and cataloged results. To complete this task, Hyper-Text Markup Language (HTML) and Cascading Style Sheets (CSS) were used as primary resources. HTML permitted documents to be formatted and displayed on the web, while CSS allowed the branding of the work for this particular lab and maintenance of a common, coherent web look.