APPLYING BIOINFORMATICS AND COMPUTATIONAL BIOLOGY TO STUDY HIV/AIDS

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This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. This project focuses upon Research in Computational Epidemiology with an emphasis on a health disparity disease of major concern, that of HIV/AIDS. There are three specific aims addressed in this project year. 1) Molecular Epidemiologic Problem Oriented Approach (EPOA) methodology of HIV/AIDS: Problem Identification and Problem Management/solution triads are the back borne of EPOA. The Problem Identification Triad is composed of the agent, host and environment pillars. Problem Management/solution Triad is composed of therapeutics, prevention/control and the health maintenance/promotion pillars. 2) Microepidemiologic Computational Modeling of HIV/AIDS: Sequence of dynamics and events within the CD4+ at the molecular level based on molecular EPOA of HIV/AIDS (item 1 above) have been reviewed and data such as the process of protein synthesis rate, enzymes involved, etc. in each of the six steps necessary for the differential equation has been collected. 3) HAART Therapies for HIV/AIDS: Which combination is the most effective? We developed various statistical models using SAS procedures. We determined the effect of time on two variables. Regression models were developed to determine the relationship between CD4+ and viral load. 4) Use of Artificial Intelligence Techniques in HAART Efficacy: Using neural networks we have developed preliminary models that predict CD4+ contents and viral load in HIV/AIDS patients. 5) Development of a systems dynamics model for HIV/AIDS with a focus on the macro-epidemiology of AIDS in African Americans has been developed.