There are many active research projects accessing and applying shared ADNI data. Use the search above to find specific research focuses on the active ADNI investigations. This information is requested annually as a requirement for data access.
| Principal Investigator | |
| Principal Investigator's Name: | Takis Benos |
| Institution: | University of Pittsburgh |
| Department: | Computattional and Systems Biology |
| Country: | |
| Proposed Analysis: | We are developing graph learning methods for the analysis of mixed data (continuous and discrete variables). Our algorithm, CausalMGM, has been successfully applied to various clinical problems (see references below). We have recently extended our framework to incorporate image data and we would like to a test its applicability to the ADNI dataset. References A. METHODOLOGY Learning undirected graphs with mixed data (MGM) Sedgewick et al, 2016, BMC Bioinformatics https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-016-1039-0 Learning directed graphs with mixed data (CausalMGM) Sedgewick et al, 2019, Bioinformatics https://academic.oup.com/bioinformatics/article-abstract/35/7/1204/5091182?redirectedFrom=fulltext Learning directed graphs with mixed data and latent confounders (MGM-FCI-MAX) Raghu et al, 2018, Int J Data Sci and Analytics https://link.springer.com/content/pdf/10.1007%2Fs41060-018-0104-3.pdf Incorporating priors in graph learning (piMGM) Manatakis, Raghu, Benos, 2018, Bioinformatics https://academic.oup.com/bioinformatics/article/34/17/i848/5093235 B. MEDICAL APPLICATIONS Identifying microbiome and clinical factors directly linked to pneumonia in ICU patients Kitsios et al, 2018, Frontiers in Microbiology https://www.frontiersin.org/articles/10.3389/fmicb.2018.01413/pdf Predicting cancer status of indeterminate nodules from low-dose CT scan data and clinical variables Raghu, (...), Benos(*), Wilson, 2019, Thorax https://thorax.bmj.com/content/thoraxjnl/early/2019/03/12/thoraxjnl-2018-212638.full.pdf Identify biomarkers (a PARP1 SNP) highly predictive of non-response to chemotherapy in cancer patients Abecassis, Sedgewick, (...), Benos, Tawbi, 2019, Scientific Reports https://www.nature.com/articles/s41598-019-39542-2.pdf Identify baseline factors that are directly linked to FEV1 longitudinal decline in COPD patients Sedgewick, (...), Benos, 2018, Bioinformatics https://academic.oup.com/bioinformatics/advance-article-abstract/doi/10.1093/bioinformatics/bty769/5091182?redirectedFrom=fulltext Predictive gene expression signatures of statin sensitivity in cancer cell lines Raghu, (...), Benos, Oltvai, 2018, Biochem Biophys Res Commun https://www.sciencedirect.com/science/article/pii/S0006291X1732243X |
| Additional Investigators |
