Nha Nguyen, Ph.D.
Affiliations: | 2010 | Electrical Engineering | University of Texas at Arlington, Arlington, TX, United States |
Area:
Bioinformatics Biology, Biostatistics Biology, Applied MathematicsGoogle:
"Nha Nguyen"Parents
Sign in to add mentorSoontorn Oraintara | grad student | 2010 | UT Arlington | |
(Wavelet based array comparative genomic hybridization and mass spectrometry data analysis.) |
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Publications
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Niethammer M, Tang CC, Jamora RDG, et al. (2023) A network imaging biomarker of X-linked dystonia-parkinsonism. Annals of Neurology |
Vo A, Nguyen N, Fujita K, et al. (2023) Disordered network structure and function in dystonia: pathological connectivity vs. adaptive responses. Cerebral Cortex (New York, N.Y. : 1991) |
Rus T, Mlakar J, Ležaić L, et al. (2022) Sporadic Creutzfeldt-Jakob disease is associated with reorganization of metabolic connectivity in a pathological brain network. European Journal of Neurology |
Perovnik M, Vo A, Nguyen N, et al. (2022) Automated differential diagnosis of dementia syndromes using FDG PET and machine learning. Frontiers in Aging Neuroscience. 14: 1005731 |
Rus T, Perovnik M, Vo A, et al. (2022) Disease specific and nonspecific metabolic brain networks in behavioral variant of frontotemporal dementia. Human Brain Mapping |
Vo A, Schindlbeck KA, Nguyen N, et al. (2022) Adaptive and pathological connectivity responses in Parkinson's disease brain networks. Cerebral Cortex (New York, N.Y. : 1991) |
Schindlbeck KA, Vo A, Nguyen N, et al. (2019) LRRK2 and GBA Variants Exert Distinct Influences on Parkinson's Disease-Specific Metabolic Networks. Cerebral Cortex (New York, N.Y. : 1991) |
Niethammer M, Tang CC, Vo A, et al. (2018) Gene therapy reduces Parkinson's disease symptoms by reorganizing functional brain connectivity. Science Translational Medicine. 10 |
Nguyen N, Vo A, Sun H, et al. (2017) Heavy-Tailed Noise Suppression and Derivative Wavelet Scalogram for Detecting DNA Copy Number Aberrations. Ieee/Acm Transactions On Computational Biology and Bioinformatics |
Nguyen N, Vo A, Choi I, et al. (2015) A stationary wavelet entropy-based clustering approach accurately predicts gene expression. Journal of Computational Biology : a Journal of Computational Molecular Cell Biology. 22: 236-49 |