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Developing Univariate Neurodegeneration Biomarkers with Low-Rank and Sparse Subspace Decomposition

Gang Wang, Qunxi Dong, Jianfeng Wu, Yi Su, Kewei Chen, Qingtang Su, Xiaofeng Zhang, Jinguang Hao, Tao Yao, Li Liu, Caiming Zhang, Richard J. Caselli (+2 others)
2020 Medical Image Analysis  
We propose a novel low-rank and sparse subspace decomposition method capable of stably quantifying the morphological changes induced by ADD.  ...  It supports the validity to develop sMRI-based univariate neurodegeneration biomarkers (UNB).  ...  First, it is possible to develop and apply a low-rank and sparse subspace decomposition approach to solve UNB problems.  ... 
doi:10.1016/j.media.2020.101877 pmid:33166772 pmcid:PMC7725891 fatcat:qbzguxhhz5fzrgrkmd2utf5lc4

Vulnerable Brain Networks Associated with Risk for Alzheimer's Disease [article]

Ali Mahzarnia, Jacques A Stout, Robert J Anderson, Hae Sol Moon, Zay Yar Han, Kate Beck, Jeffrey N Browndyke, David B. Dunson, Kim G Johnson, Richard J O'Brien, Alexandra Badea
2022 bioRxiv   pre-print
Sparse Canonical Correlation analysis (SCCA) revealed relationships between brain subgraphs and AD risk, with bootstrap based confidence intervals.  ...  Our sparse regression based predictive models revealed vulnerable networks associated with known risk factors.  ...  In this work we developed three main threads: sparse canonical correlation with bootstrap confidence interval estimation (SCCA), Tensor Network SCCA (TNSCCA), and predictive modeling.  ... 
doi:10.1101/2022.06.15.496331 fatcat:z3vybacagjfszhr5tv6vjmbpvy

Sparse reduced-rank regression for imaging genetics studies: models and applications

Maria Vounou, Giovanni Montana, GlaxoSmith Kline And EPSRC
2012
We present a novel statistical technique; the sparse reduced rank regression (sRRR) model which is a strategy for multivariate modelling of high-dimensional imaging responses and genetic predictors.  ...  Using simulation procedures that accurately reflect realistic imaging genetics data, we present detailed evaluations of the sRRR method in comparison with the more traditional univariate linear modelling  ...  by assuming a low rank representation.  ... 
doi:10.25560/9254 fatcat:ztp262blyzb23h6n5lfh6z3ciq

On the structure of natural human movement

Andreas Alexander Christian Thomik, Aldo Faisal, Fonds National De La Recherche Luxembourg
2018
To investigate this idea, we develop an algorithm for unsupervised identification of sparse structures in natural movement data.  ...  Understanding of human motor control is central to neuroscience with strong implications in the fields of medicine, robotics and evolution.  ...  "Towards neurobehavioral biomarkers for longitudi- nal monitoring of neurodegeneration with wearable body sensor networks."  ... 
doi:10.25560/61827 fatcat:ssrdhc5czvhk3dq65lnevwlooi

Network approaches to understanding the functional effects of focal brain lesions

Michael Gavin Hart, Apollo-University Of Cambridge Repository, Apollo-University Of Cambridge Repository, John Suckling
2018
Adolescent brain development demonstrated discrete dynamics with distinct gender specific and age-gender interactions.  ...  This datasets for this thesis include a clinical population with focal brain tumours and a cohort focused on healthy adolescent brain development.  ...  Small world characteristics and sparse networks are complimentary features in that they demonstrate how simultaneous segregation and integration can be achieved at a low cost of connections.  ... 
doi:10.17863/cam.21095 fatcat:ttgdreo6yffyhlph5ciqpuv3fm

In-silico models for the characterization of compounds interfering with clinical relevant ABC-multidrug-transporters

Michael Alexander Demel
2013 unpublished
From a methodological viewpoint the thesis concentrates on the assessment of different feature selection methods, descriptor development (extension of the SIBAR approach), and evaluation of distance-to-model  ...  In-silico methods have gained a lot of acceptance in the last years with respect to understand the molecular triggers that drive biological activity of small molecules on the one hand but also with respect  ...  Acknowledgement This work was supported by grants from the Austrian Promotion Agency (B1-812074) and from the Austrian Science Fund (L344-N17).  ... 
doi:10.25365/thesis.30426 fatcat:pkwghfepojf75ag3qerzsd3emm