Roumyana Kirova

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The wealth of genomic technologies has enabled biologists to rapidly ascribe phenotypic characters to biological substrates. Central to effective biological investigation is the operational definition of the process under investigation. We propose an elucidation of categories of biological characters, including disease relevant traits, based on natural(More)
UNLABELLED The liver is the primary site for the metabolism of nutrients, drugs, and chemical agents. Although metabolic pathways are complex and tightly regulated, genetic variation among individuals, reflected in variations in gene expression levels, introduces complexity into research on liver disease. This study dissected genetic networks that control(More)
The data-mining challenge presented is composed of two fundamental problems. Problem one is the separation of forty-one subjects into two classifications based on the data produced by the mass spectrometry of protein samples from each subject. Problem two is to find the specific differences between protein expression data of two sets of subjects. In each(More)
The Pax6 transcription factor is expressed in cerebellar granule cells and when mutated, as in the Sey/Sey mouse, produces granule cells with disturbed survival and migration and with defects in neurite extension. The impact of Pax6 on other genes in the context of cerebellar development has not been identified. In this study, we performed transcriptome(More)
The problem of computing logical network models to account for temporal dependencies among interacting genes and environmental stimuli from high-throughput transcriptomic data is addressed. A logical network reconstruction algorithm was developed that uses the statistical significance as a criterion for network selection to avoid false interactions arising(More)
We address the computational problems of discretizing continuous random variables and identifying a logical network model to account for temporal dependencies among genes and environmental stimuli from high-throughput transcriptome data. These new algorithms were applied to real biological data from an analysis of the molecular response to alcohol. Our(More)
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