Catherine Putonti
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Assistant Professor Ph.D. 2006, University of Houston Bioinformatics Phone: 773.508.3277 Fax: 773.508.3646 E-mail: cputonti@luc.edu |
RESEARCH INTERESTS
The primary area of my current research is computational biology. As a result of recent advances in sequencing techniques, the rate in which new biological data is becoming available far exceeds the rate in which one can perform analyses. Examining the wealth of information contained within genomic sequences presents numerous computational challenges necessitating the development of new algorithms and data structures. My current studies focus on the distribution, compositional features and characteristics of short subsequences (n-mers or motifs) within genomic sequences. Specifically, I have concentrated my scientific interests to three areas.1. Designing Assays for Pathogen Detection. In recent years, the majority of new pathogen identification and diagnosis assays have used nucleic acid-based technologies Designing such assays is computationally challenging. The problem is compounded by the difficulty in finding a single, unique genomic sequence that is present simultaneously in all the genomes of a species of closely related pathogens and absent in the genomes of the host or the organisms that contribute to the sample background. A set of novel algorithms and data structures have been developed which make it possible to efficiently calculate the distance or the number of base changes necessary to “convert” the signature to the closest sequence found in the host/background genome where all possible base changes and combinations of base changes are considered. Using this new suite of tools, ultraspecific primers/probes have been designed for the identification of several different viral and bacterial pathogenic organisms.
2. Identifying Genomic Regions of Unusual Compositional Properties. The frequency distribution of n-mers within genomic sequences has been applied in the literature as a means to describe a particular organism. Analysis of the distribution of n-mer frequencies provides a powerful tool in comparing genomic sequences. Inconsistencies in the composition of a genomic sequence, e.g. differences in di- and tri-nucleotide frequencies, G+C content, amino acid biases, etc., have been used numerous times in the literature to search for horizontal gene transfer (HGT). While this analysis has traditionally been applied exclusively to bacterial genomes, recent studies have begun to apply this alignment-free approach to the genomes of larger eukaryotic organisms as a means of examining the evolution of species at the chromosomal and whole genomic level.
REPRESENTATIVE PUBLICATIONS
Reed, C., Fofanov, V., Putonti, C., Chumakov, S., Slezak, T., Fofanov, Y. Effect of the mutation rate and background size on the quality of pathogen identification. Bioinformatics. IN PRESS.Añez, M., Putonti, C., Fox, G.E., Fofanov, Y., Willson, R.C. Exhaustive Computational Identification of Pathogen Sequences Distant from Background Genomes: Identification of Human-blind Dengue PCR Primers. J. Biotechnol. IN PRESS.
Putonti, C., Luo, Y., Katili, C., Chumakov, S., Fox, G.E., Graur, D., Fofanov, Y. A computational tool for the genomic identification of regions of unusual compositional properties and its utilization in the detection of horizontally transferred sequences. Mol Biol Evol. 2006; 23(10): 1863-1868.
Putonti, C., Chumakov, S., Mitra, R., Fox, G.E., Willson, R.C., Fofanov, Y. Human-blind probes and primers for Dengue virus identification: Exhaustive analysis of subsequences present in the human and 83 Dengue genome sequences. FEBS J. 2006; 273(2): 398-408.
Chumakov, S., Belapurkar, C., Putonti, C., Li, T.-B., Pettitt, B.M., Fox, G.E., Willson, R.C., Fofanov, Y. Theoretical Basis for Universal Identification Systems for Bacteria and Viruses. Journal of Biological Physics and Chemistry 2005; 5(4): 121-128.
Fig. Using computationally identified “ultraspecific” signatures as, for instance PCR primers, it is possible to detect the presence of pathogenic organisms in complex samples. (Photo by: Dr. Jerome Crowder)