January 14-18, 2006
Town & Country Convention Center
San Diego, CA
As the area of bioinformatics has become more mature, there has been an increased acceptance of how sequence data should be analyzed and reported. These accepted methodologies has allowed for the computational automation of many types of annotation pipelines. For this study, LASS1 was selected to illustrate the usefulness of building flexible computational workflows with a graphical interface. A set of bioinformatics protocols (i.e., pipelines) were created to characterize and explore newly identified LASS1 orthologs. Protocol #1 used BLAST programs to find putative LASS1 sequences in genomic and EST databases. The search identified similar sequences from organisms such as puffer fish, zebra fish, mosquito, and drosophila. Protocol #2 created a multiple sequence alignment of these protein ortholog sequences, and a HMM profile was generated. The HMM profile was used to identify the LAG1 ortholog in Arabidopsis thaliana. Also, in Protocol #2 a phylogenetic tree program was integrated into the pipeline to show the relatedness of the protein sequences relative to each organism. Protocol #3 was constructed to summarize and assemble the sequence properties (molecular weight, isoelectric point, etc.) of each ortholog protein in a single report. Protocol #4 was built to elucidate the types of helices predicted based on length and organism. And, Protocol #5 was used to search for LASS1 information at PubMed, NIH Crisp Grants, and USPTO simultaneously.