Integrated Tools For Genomic Information Analysis

Genomic information provides the first stage in understanding the instructions for the synthesis of all of life's molecular machines and the systems needed to control and operate them. The interaction among biological, physical and computing sciences has provided the bases for the creation of a great number of bioinformatic tools [1]. Our laboratory uses the multicellular microorganism Trichoderma reesei as a model system to study the genomic regulatory networks for energy production in eukaryotes. During the developing of an “Expressed Sequence Tags” (ESTs) database for T. reesei [2], we achieved a vast amount of information, making it almost impossible to handle all the data obtained without the use of computational tools. A software methodology for genomic information analysis was developed based on the Integration Definition for Function Modeling [3] (IDEF) approach and the results are fully available at http://trichoderma.iq.usp.br. The IDEF was developed by the United States Air Force and has been used to model a wide variety of automated and non-automated systems. The obtained flux diagrams detail each step of the data analyses, which include: (i) quality analyses of electrophoretograms by the Phred software [4]; (ii) sequence clustering by the Phrap software [5]; (iii) gene identification by the Blast client software, provided by NCBI [6]; (iv) and classification of the genes according to their putative function. Phred software reads DNA sequencer trace data, calls bases, assigns quality values to the bases and writes the base calls and quality values to files in either FASTA or PHD format. Phrap software is a program to assemble shotgun DNA sequence data using the PHD files generated by Phred. The Blast client software compares sequences against the GenBank non-redundant protein database. Based on this methodology, UML [7] structures wereestablished to help specify, visualize and document the softwaresystem, including its structure and design. Thus, researchers withlittle genetic expertise from biological, physical and computingscience can achieve technical understanding of the genomicanalysis software. REFERENCES[1]Setubal, João Carlos, Medanis, João, “Introduction tocomputational molecular biology”, PWS Pub., Boston, 1997 [2]Chambergo, Felipe S. et al., “Elucidation of the metabolic fateof glucose in the filamentous fungus Trichoderma reeseiusing expressed sequence tag (EST) analysis and cDNAmicroarrays”, Journal of Biological Chemistry, 277(16), p.13983-13988, 2002 [3]IDEF Family of Methods, http://www.idef.com/idef0.html[4]Green, Phil, Ewing, Brent, “PHRED Documentation”,http://www.phrap.org/phrap.docs/phred.html [5]Green, Phil, “Documentation for PHRAP andCROSS_MATCH”,http://www.phrap.org/phrap.docs/phrap.html [6]National Center for Biotechnology Information,http://www.ncbi.nlm.nih.gov/BLAST/ [7]Unified Modeling Language, http://www.uml.org