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My general research interest encompasses the development of machine learning techniques to resolve problems in bioinformatics/computational biology and text classification. I am interested in applying
these computational tools to the analysis of complex and varied biomedical data, in order to establish gene-based diagnostic tests and therapeutic strategies for improving public health, by helping to understand the genetic foundation of diseases. These discoveries
will further enable the development of unifying global perspectives and principles in biology that can be applied to the advancement of medical research. My postdoctoral work at the Wistar Institute Cancer Center provided me with the opportunity to work with
a number of research groups on clinical projects ranging from the development of cancer diagnostics and identifying potential targets to studies on infectious diseases including extensive collaboration with investigators working on HIV. During this time,
I also developed a research program focused on identifying miRNAs and their targets.
Within bioinformatics/computational biology, my present research can be divided into two basic domains:
MicroRNA gene and target identification. Studying miRNAs and their targets is an important area of research because of their role in gene expression regulation.
Highly collaborative coding and non-coding gene expression analysis as they relate to biomedical studies. My extensive experiences collaborating with biomedical researchers at all levels put me
in a unique position to work closely within a diverse groups of bench scientists from varied disciplines as well as computational researchers
Within bioinformatics/computational biology, my present research can be divided into two basic domains: