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Evolving robust gene regulatory networks. [PDF]
Design and implementation of robust network modules is essential for construction of complex biological systems through hierarchical assembly of 'parts' and 'devices'.
Nasimul Noman +3 more
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Discovering study-specific gene regulatory networks. [PDF]
Microarrays are commonly used in biology because of their ability to simultaneously measure thousands of genes under different conditions. Due to their structure, typically containing a high amount of variables but far fewer samples, scalable network ...
Valeria Bo +5 more
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Quantum gene regulatory networks
In this work, we present a quantum circuit model for inferring gene regulatory networks (GRNs) from single-cell transcriptomic data. The model employs qubit entanglement to simulate interactions between genes, resulting in competitive performance and ...
Cristhian Roman-Vicharra, James J. Cai
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Reconstructing Dynamic Gene Regulatory Networks Using f-Divergence from Time-Series scRNA-Seq Data [PDF]
Inferring time-varying gene regulatory networks from time-series single-cell RNA sequencing (scRNA-seq) data remains a challenging task. The existing methods have notable limitations as most are either designed for reconstructing time-varying networks ...
Yunge Wang +5 more
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Glucocorticoid receptor-dependent gene regulatory networks. [PDF]
While the molecular mechanisms of glucocorticoid regulation of transcription have been studied in detail, the global networks regulated by the glucocorticoid receptor (GR) remain unknown.
Phillip Phuc Le +6 more
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The role of master regulators in gene regulatory networks [PDF]
Gene regulatory networks present a wide variety of dynamical responses to intrinsic and extrinsic perturbations. Arguably, one of the most important of such coordinated responses is the one of amplification cascades, in which activation of a few key ...
Enrique Hernández Lemus +3 more
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Inferring gene regulatory network from single-cell transcriptomes with graph autoencoder model.
The gene regulatory structure of cells involves not only the regulatory relationship between two genes, but also the cooperative associations of multiple genes.
Jiacheng Wang, Yaojia Chen, Quan Zou
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Structure learning for gene regulatory networks.
Inference of biological network structures is often performed on high-dimensional data, yet is hindered by the limited sample size of high throughput "omics" data typically available. To overcome this challenge, often referred to as the "small n, large p
Anthony Federico +3 more
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Chaotic motifs in gene regulatory networks. [PDF]
Chaos should occur often in gene regulatory networks (GRNs) which have been widely described by nonlinear coupled ordinary differential equations, if their dimensions are no less than 3. It is therefore puzzling that chaos has never been reported in GRNs
Zhaoyang Zhang +5 more
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Gene Self-Expressive Networks as a Generalization-Aware Tool to Model Gene Regulatory Networks
Self-expressiveness is a mathematical property that aims at characterizing the relationship between instances in a dataset. This property has been applied widely and successfully in computer-vision tasks, time-series analysis, and to infer underlying ...
Sergio Peignier, Federica Calevro
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