Publications by authors named "Nicholas Franzese"

Over the past decade, a promising line of cancer research has utilized machine learning to mine statistical patterns of mutations in cancer genomes for information. Recent work shows that these statistical patterns, commonly referred to as "mutational signatures," have diverse therapeutic potential as biomarkers for cancer therapies. However, translating this potential into reality is hindered by limited access to sequencing in the clinic.

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Characterizing cellular responses to different extrinsic signals is an active area of research, and curated pathway databases describe these complex signaling reactions. Here, we revisit a fundamental question in signaling pathway analysis: are two molecules "connected" in a network? This question is the first step towards understanding the potential influence of molecules in a pathway, and the answer depends on the choice of modeling framework. We examined the connectivity of Reactome signaling pathways using four different pathway representations.

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Motivation: Mathematical models of cellular processes can systematically predict the phenotypes of novel combinations of multi-gene mutations. Searching for informative predictions and prioritizing them for experimental validation is challenging since the number of possible combinations grows exponentially in the number of mutations. Moreover, keeping track of the crosses needed to make new mutants and planning sequences of experiments is unmanageable when the experimenter is deluged by hundreds of potentially informative predictions to test.

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The pathophysiological changes that occur during ischemic stroke can have a profound effect on the surrounding nerve tissue. To this end, we advance the hypothesis that retinal damage can occur as a consequence of ischemic stroke in animal models. We discuss the preclinical evidence over the last 3 decades supporting this hypothesis of retinal damage following ischemic stroke.

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Our understanding of biological mechanisms and treatment options for traumatic brain injury (TBI) is limited. Here, we employed quantitative real-time PCR (QRT-PCR) and immunohistochemical analyses to determine the dynamic expression of cell proliferation and apoptosis in an effort to provide insights into the therapeutic window for developing regenerative strategies for TBI. For this purpose, young adult Sprague-Dawley rats were subjected to experimental TBI using a controlled cortical impactor, then euthanized 1-48 hours after TBI for QRT-PCR and immunohistochemistry.

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