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Songjian Lu, PhD Assistant Professor

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Presentation on theme: "Songjian Lu, PhD Assistant Professor"— Presentation transcript:

1 Study cancer disease mechanisms by searching for cancer signaling pathways
Songjian Lu, PhD Assistant Professor Department of Biomedical Informatics University of Pittsburgh School of Medicine

2 The major goal of my current research
Pathway regulates the proliferation Pathway regulates the cell cycle Pathway regulates the cell death Genes related to the cell cycle Genes related to the proliferation Genes related to the cell death The major goal of my current research Re-construct the signaling pathways related to cancer development. Understand the cancer disease mechanism. Provide the potential candidates for target therapy. The basic method Apply the reverse engineering technology: Formulate the pathway reconstruction problem into the graph problems. Design efficient exact algorithms to solve the NP-hard graph problems in our models, which guarantees the optimal solutions of the models.

3 Examples of research results
Computational results: The mutation of TP53, the amplifications of MED1, YWHAZ, and PTK2 affect the cell DNA repair, mitosis, cell cycle etc. Wet-lab verification: The knockdown of MED1, PTK2 and YWHAX thwart the growth of cancer cells. Hence, they are the potential candidates for target therapy.

4 Recent publications Research funding 1.
S. Lu, K. Lu, X. Ma, N. Nystrom, X. Lu, Identifying driver genomic alterations in cancers by searching minimum-weight, mutually exclusive sets, PLOS Computational Biology (In press). 2. S. Lu, X. Lu. Using graph model to find transcription factor modules: the hitting set problem and an exact algorithm. Algorithms for Molecular Biology. 2013; 8(2). 3. S. Lu, B. Jin, L. Cowart, X. Lu. From data towards knowledge: Revealing the architecture of signaling systems by unifying knowledge mining and data mining of systematic perturbation data. PLOS One. 2013; 8(4). Research funding Developing graph models and efficient algorithms for the study of cancer disease mechanisms (PI, NIH K99/R00, 02/ /2018).


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