TY - GEN
T1 - A data-driven method to study brain structural connectivities via joint analysis of microarray data and dMRI data
AU - Li, Xiao
AU - Zhang, Tuo
AU - Liu, Tao
AU - Lv, Jinglei
AU - Hu, Xintao
AU - Guo, Lei
AU - Liu, Tianming
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/6/15
Y1 - 2016/6/15
N2 - Connective structure is an outstanding feature of the brain. Exploring the mechanism of its development and its variation across individual and species might hold the key to understanding brain functions and brain diseases. Genes are widely recognized as the fundamental regulators of the connective architecture, but it is still far from fully understanding genetics impacts on brain connectivities. Quantitative analysis of advanced imaging data, such as diffusion MRI (dMRI), provides phenotypic features and plausible clues for exploring the genetic reasons. Therefore, in this paper, we jointly analyzed dMRI data and microarray gene expression data. By developing a novel method to compare the dMRI derived structural connectivity matrix and gene expression distance matrix, we identified gene groups which might contribute to structural wiring diagram. Effectiveness and reproducibility of this method has been demonstrated.
AB - Connective structure is an outstanding feature of the brain. Exploring the mechanism of its development and its variation across individual and species might hold the key to understanding brain functions and brain diseases. Genes are widely recognized as the fundamental regulators of the connective architecture, but it is still far from fully understanding genetics impacts on brain connectivities. Quantitative analysis of advanced imaging data, such as diffusion MRI (dMRI), provides phenotypic features and plausible clues for exploring the genetic reasons. Therefore, in this paper, we jointly analyzed dMRI data and microarray gene expression data. By developing a novel method to compare the dMRI derived structural connectivity matrix and gene expression distance matrix, we identified gene groups which might contribute to structural wiring diagram. Effectiveness and reproducibility of this method has been demonstrated.
KW - brain structural connectivity
KW - dMRI
KW - joint analysis
KW - microarray
UR - http://www.scopus.com/inward/record.url?scp=84978435064&partnerID=8YFLogxK
U2 - 10.1109/ISBI.2016.7493394
DO - 10.1109/ISBI.2016.7493394
M3 - 会议稿件
AN - SCOPUS:84978435064
T3 - Proceedings - International Symposium on Biomedical Imaging
SP - 829
EP - 832
BT - 2016 IEEE International Symposium on Biomedical Imaging
PB - IEEE Computer Society
T2 - 2016 IEEE 13th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016
Y2 - 13 April 2016 through 16 April 2016
ER -