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Advisor Information
Dhundy Kiran Bastola
Location
Dr. C.C. and Mabel L. Criss Library
Presentation Type
Poster
Start Date
3-3-2017 12:30 PM
End Date
3-3-2017 1:45 PM
Abstract
Molecular Identification of Pathogenic Organisms (MIPO) is a computational tool developed by the bioinformatics group at UNO. It is used in the identification of pathogenic organisms based on the DNA sequence the pathogen contains in its body. However, these pathogenic organisms are constantly evolving in nature primarily due to the introduction of mutation at the DNA level followed by the natural selection. Consequently, annotation of organism based on a small fragment of DNA alone may be limiting to correctly identify them from a mixed population that exists in nature. In the present study, we add morphological features of organism obtained from “expert crowd” to the existing sequence data for that organism. We hypothesize that this approach will increase the sensitivity of MIPO in correctly identifying pathogenic organisms. We have developed multiple web-services (service offered by an electronic device to another electronic device) to collect and populate MIPO-Database from standard data repositories like the GenBank and /or the “expert crowd” connected thought the web-interface. Preliminary result indicates that there is value in integrating morphological data relating to the organism when trying to identify closely related species.
Molecular identification of Pathogenic Organism(MIPO) - Engaging a Crowd to build knowledge base
Dr. C.C. and Mabel L. Criss Library
Molecular Identification of Pathogenic Organisms (MIPO) is a computational tool developed by the bioinformatics group at UNO. It is used in the identification of pathogenic organisms based on the DNA sequence the pathogen contains in its body. However, these pathogenic organisms are constantly evolving in nature primarily due to the introduction of mutation at the DNA level followed by the natural selection. Consequently, annotation of organism based on a small fragment of DNA alone may be limiting to correctly identify them from a mixed population that exists in nature. In the present study, we add morphological features of organism obtained from “expert crowd” to the existing sequence data for that organism. We hypothesize that this approach will increase the sensitivity of MIPO in correctly identifying pathogenic organisms. We have developed multiple web-services (service offered by an electronic device to another electronic device) to collect and populate MIPO-Database from standard data repositories like the GenBank and /or the “expert crowd” connected thought the web-interface. Preliminary result indicates that there is value in integrating morphological data relating to the organism when trying to identify closely related species.