Computational approaches for intelligent processing of biomedical data

TitleComputational approaches for intelligent processing of biomedical data
Publication TypeThesis
Year of Publication2015
AuthorsMirina, A
AdvisorBergman, A
Number of Pages111
Date Published2015
UniversityYeshiva University
CityNew York
Thesis TypePh.D.
Accession Number1749893145
KeywordsGenetics, Health Conditions and Status, Other

The rapid development of novel experimental techniques has led to the generation of an abundance of biological data, which holds great potential for elucidating many scientific problems. The analysis of such complex heterogeneous information, which we often have to deal with, requires appropriate state-of-the-art analytical methods. Here we demonstrate how an unconventional approach and intelligent data processing can lead to meaningful results. This work includes three major parts. In the first part we describe a correction methodology for genome-wide association studies (GWAS). We demonstrate the existing bias for the selection of larger genes for downstream analyses in GWA studies and propose a method to adjust for this bias. Thus, we effectively show the need for data preprocessing in order to obtain a biologically relevant result. In the second part, building on the results obtained in the first part, we attempt to elucidate the underlying mechanisms of aging and longevity by conducting a longevity GWAS. Here we took an unconventional approach to the GWAS analysis by applying the idea of genetic buffering. Doing this allowed us to identify pairs of genetic markers that play a role in longevity. Furthermore, we were able to confirm some of them by means of a downstream network analysis. In the third and final part, we discuss the characteristics of chronic lymphocytic leukemia (CLL) B-cells and perform clustering analysis based on immunoglobulin (Ig) mutation patterns. By comparing the sequences of Ig of CLL patients and healthy donors, we show that different Ig heavy chain (IGHV) regions in CLL exhibit similarities with different B-cell subtypes of healthy donors, which raised a question about the single origin of CLL cases.


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Short TitleComputational approaches for intelligent processing of biomedical data
Citation Key6009