Associative conditioning in gene regulatory network models increases integrative causal emergence. [PDF]
Pigozzi F, Goldstein A, Levin M.
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Precision in Delivery, Variability in Response: A Multiscale Mechanistic Framework for Neuronavigated Transcranial Magnetic Stimulation. [PDF]
Setlak MK +3 more
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Morphometric Inverse Divergence Networks Combined with HYDRA Identify Parkinson's Disease Subtypes with Distinct Transcriptomic and Serum Biomarker Profiles. [PDF]
Bianco MG +9 more
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Identifying regulators of associative learning using a protein-labelling approach in <i>Caenorhabditis elegans</i>. [PDF]
Rahmani A +7 more
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Reconstruction of gene network associated with Parkinson disease for gene targets search
Biomeditsinskaya Khimiya, 2021Accumulation 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
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Gene Network Modules Associated to DPSCs Differentiation
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Temporal association rules for gene regulatory networks
2008 4th International IEEE Conference Intelligent Systems, 2008DNA 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.
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