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Morphometric Inverse Divergence Networks Combined with HYDRA Identify Parkinson's Disease Subtypes with Distinct Transcriptomic and Serum Biomarker Profiles. [PDF]

open access: yesInt J Mol Sci
Bianco MG   +9 more
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Reconstruction of gene network associated with Parkinson disease for gene targets search

Biomeditsinskaya Khimiya, 2021
Accumulation of genetic data in the field of Parkinson's disease research culminated in identifying risk factors and confident prediction of the disease occurrence. To find new gene-targets for diagnostics and therapy we have to reconstruct gene network of the disease, to cluster genes in the network, to reveal key (hub) genes with largest number of
Y L, Orlov   +5 more
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Identification of gene networks associated with erythroid differentiation

Blood Cells, Molecules, and Diseases, 2009
Erythropoiesis is a multistep process involving a large number of genes, which balance between proliferation, differentiation and survival of the erythroid cells. To understand the molecular mechanisms of erythropoiesis and related pathological aberrations, we analyzed three stages of in vitro differentiating human erythroid cells by expression ...
Shoshana, Peller   +6 more
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Gene Network Modules Associated to DPSCs Differentiation

2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC), 2017
Dental pulp stem cells (DPSCs) are stem cellspresent in the dental pulp and have same renewal anddifferentiating properties as bone marrow cells. Hence, DPSCs canbe used for future regenerative therapies of various diseases.Previous studies show that DPSCs would lose their differentiationcapability during long-term passage when they were cultured ...
Wenjing Xu   +7 more
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Temporal association rules for gene regulatory networks

2008 4th International IEEE Conference Intelligent Systems, 2008
DNA hybridization arrays simultaneously measure the expression level for thousands of genes. A great challenge in the bioinformatics field is to discover gene interactions from such measurements and estimate gene networks. In this paper, we exploit data mining techniques for discovering interactions among genes based on multiple expression measurements.
BARALIS, ELENA MARIA   +2 more
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