The Biostatistics, Bioinformatics and Data Management (BBDM) Core will serve the program by providing state-of-the-art biostatistical analysis of the large and complex datasets being assembled in this program project, by generating models of protein-interaction-networks, and by managing the database for facile interrogation by all investigators. There will be great need for data to stream smoothly among the three research projects. The data stream will be dynamic with nevy information being added as experiments are completed. The BBDM core will be chargedwith designing and maintaining a database that can be regularly accessed by program investigators. Biostatistical comparisons among different melanocyte preparations and melanoma lines will be done to identify components of the system of response to DMAdamage that provide maximal predictive value for determining cellular risk of oncogenic transformation after exposure to UV. The BBDM core will insure that experiments are properly designed to gain maximal predictive power and develop new statistical tools to analyze the complex and varied datasets being produced by program investigators. The BBDM core leverages computational power and networking capabilities in the Renaissance Computing Institute to provide program investigators with the ability to visualize and analyze the networks of interacting proteins in the various systems of response to DNA damage.
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| Lin, Ja-An; Zhu, Hongtu; Mihye, Ahn et al. (2014) Functional-mixed effects models for candidate genetic mapping in imaging genetic studies. Genet Epidemiol 38:680-91 |
| Nikolaishvilli-Feinberg, Nana; Cohen, Stephanie M; Midkiff, Bentley et al. (2014) Development of DNA damage response signaling biomarkers using automated, quantitative image analysis. J Histochem Cytochem 62:185-96 |
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| Chen, Liddy M; Ibrahim, Joseph G; Chu, Haitao (2014) Flexible stopping boundaries when changing primary endpoints after unblinded interim analyses. J Biopharm Stat 24:817-33 |
| Kricker, Anne; Armstrong, Bruce K; Goumas, Chris et al. (2013) Survival for patients with single and multiple primary melanomas: the genes, environment, and melanoma study. JAMA Dermatol 149:921-7 |
| Schlegel, Jennifer; Sambade, Maria J; Sather, Susan et al. (2013) MERTK receptor tyrosine kinase is a therapeutic target in melanoma. J Clin Invest 123:2257-67 |
| Omolo, Bernard; Carson, Craig; Chu, Haitao et al. (2013) A prognostic signature of G(2) checkpoint function in melanoma cell lines. Cell Cycle 12:1071-82 |
| Smith-Roe, Stephanie L; Patel, Shivani S; Zhou, Yingchun et al. (2013) Separation of intra-S checkpoint protein contributions to DNA replication fork protection and genomic stability in normal human fibroblasts. Cell Cycle 12:332-45 |
| Lakhter, Alexander J; Sahu, Ravi P; Sun, Yang et al. (2013) Chloroquine promotes apoptosis in melanoma cells by inhibiting BH3 domain-mediated PUMA degradation. J Invest Dermatol 133:2247-54 |
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