skip to main content
Explore Scholarly Publications and Datasets in the NSF-PAR

  • Home
  • Search Results
  • Page 1 of 1

Search for: All records

Creators/Authors contains: "Du, L."

Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?

Some links on this page may take you to non-federal websites. Their policies may differ from this site.

  1. ; ; ; ; ( , Proceedings of the 2021 Summer Biomechanics, Bioengineering, and Biotransport Conference (SB3C))
    Accepted Manuscript Full Text Available
  2. ; ; ( , IEEE transactions on transportation electrification)
    Full Text Available 
  3. ; ; ; ; ( , Proceedings of the 2020 SEM Annual Conference & Exposition on Experimental and Applied Mechanics)
    Accepted Manuscript Full Text Available
  4. ; ; ; ; ; ; ; ; ; ; et al ( , Physical Review C)
    Full Text Available 
  5. ; ; ; ; ; ; ; ; ( , International Conference on Medical Image Computing and Computer-Assisted Intervention)
    Brain imaging genetics is an important research topic in brain science, which combines genetic variations and brain structures or functions to uncover the genetic basis of brain disorders. Imaging data collected by different technologies, measuring the same brain distinctly, might carry complementary but different information. Unfortunately, we do not know the extent to which phenotypic variance is shared among multiple imaging modalities, which might trace back to the complex genetic mechanism. In this study, we propose a novel dirty multi-task SCCA to analyze imaging genetics problems with multiple modalities of brain imaging quantitative traits (QTs) involved. The proposed method canmore »not only identify the shared SNPs and QTs across multiple modalities, but also identify the modality-specific SNPs and QTs, showing a flexible capability of discovering the complex multi-SNP-multi-QT associations. Compared with the multi-view SCCA and multi-task SCCA, our method shows better canonical correlation coefficients and canonical weights on both synthetic and real neuroimaging genetic data. This demonstrates that the proposed dirty multi-task SCCA could be a meaningful and powerful alternative method in multi-modal brain imaging genetics.« less
    Full Text Available 
  6. ; ; ; ; ; ; ; ; ; ; et al ( , Physical Review Letters)
    Full Text Available 
  7. ; ; ; ; ; ; ; ; ; ; et al ( , Physical Review C)
    Full Text Available 
  8. ; ; ; ( , Advances in neural information processing systems)
    Accepted Manuscript Full Text Available
  9. ; ; ; ; ; ; ; ; ; ; et al ( , Physical Review C)
    Full Text Available