A5012996112- Tensor decomposition and applications
- Advanced Neuroimaging Techniques and Applications
- Blind Source Separation Techniques
- Sparse and Compressive Sensing Techniques
- Botany and Plant Ecology Studies
- Neural dynamics and brain function
- Plant Ecology and Taxonomy Studies
- Neonatal and fetal brain pathology
- Infant Development and Preterm Care
- Functional Brain Connectivity Studies
- Computational Physics and Python Applications
- Photosynthetic Processes and Mechanisms
- Plant-Microbe Interactions and Immunity
- Genomics and Phylogenetic Studies
- Plant nutrient uptake and metabolism
- Health, Environment, Cognitive Aging
- Ecology and biodiversity studies
University of Maryland, Baltimore County
2020-2024
J. Craig Venter Institute
2016
Royal Botanic Gardens, Kew
2015
<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Objective:</i> Brain function is understood to be regulated by complex spatiotemporal dynamics, and can characterized a combination of observed brain response patterns in time space. Magnetoencephalography (MEG), with its high temporal resolution, functional magnetic resonance imaging (fMRI), spatial are complementary techniques great potential reveal information about dynamics. Hence, the...
ThaleMine (https://apps.araport.org/thalemine/) is a comprehensive data warehouse that integrates wide array of genomic information the model plant Arabidopsis thaliana. The collection currently includes latest structural and functional annotation from Araport11 update, Col-0 genome sequence, RNA-seq expression, co-expression, protein interactions, homologs, pathways, publications, alleles, germplasm phenotypes. are collected variety public resources. Users can browse gene-specific through...
This paper proposes an independent component analysis (ICA)-based framework for exploring associations between neural signals measured with magnetoencephalography (MEG) and non-neuroimaging data of healthy subjects. Our proposed contains methods subject group identification, latent source estimation MEG, discriminatory visualization. Hierarchical clustering on principal components (HCPC) is used to cluster groups based cognitive scores, ICA performed MEG evoked responses such that not only...
Tensor representations have proven useful for many problems, including data completion. A promising application tensor completion is functional magnetic resonance imaging (fMRI) that has an inherent four-dimensional (4D) structure and prone to missing voxels regions due issues in acquisition. key component of successful a rank estimation. While widely used as convex relaxation the rank, nuclear norm (TNN) imposes strong low-rank constraints on all modes be simultaneously often leads...
Functional magnetic resonance imaging (fMRI) is a powerful, noninvasive tool that has significantly contributed to the understanding of human brain. FMRI data provide sequence whole-brain volumes over time and hence are inherently four dimensional (4D). Missing in fMRI experiments arise from image acquisition limits, susceptibility motion artifacts or during confounding noise removal. Hence, significant brain regions may be excluded data, which can seriously undermine quality subsequent...