Center Description: Technology and analytical advances have greatly facilitated the rapid progress of data sciences and health sciences, e.g., rapid accumulation of multi-modal high dimensional data in genomics, transcriptomics, epigenomics, proteomics, metabolomics, gut metagenomics, single cell sequencing and spatial sequencing, electronic health/medical records – EHR or EMR. Data sciences have produced advanced analytics for artificial intelligence (AI), machine learning (ML) and deep learning (DL) that can extract intrinsic patterns of complex and often non-linear relationship among multi-omics for diagnosis, prediction, and inferences of disease/health causality and mechanisms. Integrating health sciences and data sciences in order to harness the greater power of the ever increasingly large volume and complexity of big data in health research and ever evolving capability of data sciences imposes great challenges.
The overarching goal of TIIDHS is to develop a center to perform cutting edge convergence research to innovatively integrate data sciences and health sciences to position Tulane competitively for the emerging challenges and opportunities that are relevant and significant for research across Tulane schools (such as SOM, SSE, SPHTM). The proposed center is the first of its kind in US.
Center Purpose: Our proposed Center supports the mission of Tulane, and the strategic vision of Convergence Research to address pressing health concerns and societal needs.
Center Directors: Hong-Wen Deng (SOM), Tanika Kelly (SPHTM), Yu-Ping Wang (SSE)
Center Team Members: Lydia Bazzano, Hong-Wen Deng, Lu Qi, Hui Shen, Yu-Ping Wang, Zhengming Ding, Zizhan Zheng, XW Liu, Patrice "Patrick" Delafontaine, David Crosslin, Xiao-Ming Yin, JQ Brown, D Gaver
Partnering Schools: Tulane School of Public Health and Tropical Medicine Tulane School of Medicine Dean Thomas LaVeist Signature: Dean Lee Hamm Signature: Tulane school of Science and Engineering - Dean Kimberly Foster:
