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Gene network reconstruction
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Ebook "Frontiers in computational and systems biology" consists of 19 chapters and covers a wide spectrum of topics. Described applications of an RNA structure sampling algorithm to the rational design of short interfering RNAs for gene silencing by RNA interference and to target identification for microRNAs that play important roles in posttranscriptional gene regulation.
411p
ladongphongthanh1008
22-04-2024
5
2
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Alterations in genetic and epigenetic landscapes are known to contribute to the development of different types of cancer. However, the mechanistic links between transcription factors and the epigenome which coordinate the deregulation of gene networks during cell transformation are largely unknown.
16p
vioraclene
31-03-2024
2
2
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Gene co-expression networks capture biological relationships between genes and are important tools in predicting gene function and understanding disease mechanisms. We show that technical and biological artifacts in gene expression data confound commonly used network reconstruction algorithms.
6p
vigalileogalilei
27-02-2022
14
1
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Constructing gene coexpression networks is a powerful approach for analyzing high-throughput gene expression data towards module identification, gene function prediction, and disease-gene prioritization.
26p
viarchimedes
26-01-2022
8
0
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Ablepharus Lichtenstein, 1823, which includes ten species, is distributed in eastern Europe and Asia. Four species are recorded in Turkey: A. kitaibelii, A. chernovi, A. bivittatus, and A. budaki. After molecular and morphological studies in Anatolia, the phylogenetic relationship of the genus is still very complicated. Here, we investigate the taxonomic status of Ablepharus in Anatolia using morphological and molecular methods. The genetic structure of Ablepharus populations in Anatolia was analyzed using both the nuclear (CMOS) and mitochondrial (cyt b and COI) gene regions.
12p
dolomite36
30-12-2021
16
1
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The reconstruction of gene regulatory network (GRN) from gene expression data can discover regulatory relationships among genes and gain deep insights into the complicated regulation mechanism of life. However, it is still a great challenge in systems biology and bioinformatics. During the past years, numerous computational approaches have been developed for this goal, and Bayesian network (BN) methods draw most of attention among these methods because of its inherent probability characteristics.
14p
vilarryellison
29-10-2021
15
0
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Inference of protein’s membership in metabolic pathways has become an important task in functional annotation of protein. The membership information can provide valuable context to the basic functional annotation and also aid reconstruction of incomplete pathways. Previous works have shown success of inference by using various similarity measures of gene ontology.
10p
vitzuyu2711
29-09-2021
19
1
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We consider the problem of reconstructing a gene regulatory network structure from limited time series gene expression data, without any a priori knowledge of connectivity. We assume that the network is sparse, meaning the connectivity among genes is much less than full connectivity.
22p
vikentucky2711
26-11-2020
16
0
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In the last decade, a great number of methods for reconstructing gene regulatory networks from expression data have been proposed. However, very few tools and datasets allow to evaluate accurately and reproducibly those methods. Hence, we propose here a new tool, able to perform a systematic, yet fully reproducible, evaluation of transcriptional network inference methods.
15p
vikentucky2711
24-11-2020
8
1
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ntegratively analyzing multiple gene expression, microarray datasets in order to reconstruct gene-gene interaction networks. Integrating multiple datasets is generally believed to provide increased statistical power and to lead to a better characterization of the system under study.
19p
vioklahoma2711
19-11-2020
11
1
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Rapid technological innovation for the generation of single-cell genomics data presents new challenges and opportunities for bioinformatics analysis. One such area lies in the development of new ways to train gene regulatory networks.
18p
vioklahoma2711
19-11-2020
8
0
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A gene regulatory network (GRN) represents interactions of genes inside a cell or tissue, in which vertexes and edges stand for genes and their regulatory interactions respectively. Reconstruction of gene regulatory networks, in particular, genome-scale networks, is essential for comparative exploration of different species and mechanistic investigation of biological processes.
8p
vioklahoma2711
19-11-2020
7
1
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The post-genomic era with its wealth of sequences gave rise to a broad range of protein residueresidue contact detecting methods. Although various coevolution methods such as PSICOV, DCA and plmDCA provide correct contact predictions, they do not completely overlap.
9p
vioklahoma2711
19-11-2020
6
1
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Network component analysis (NCA) became a popular tool to understand complex regulatory networks. The method uses high-throughput gene expression data and a priori topology to reconstruct transcription factor activity profiles. Current NCA algorithms are constrained by several conditions posed on the network topology, to guarantee unique reconstruction (termed compliancy).
13p
vioklahoma2711
19-11-2020
13
1
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Gene regulatory networks reveal how genes work together to carry out their biological functions. Reconstructions of gene networks from gene expression data greatly facilitate our understanding of underlying biological mechanisms and provide new opportunities for biomarker and drug discoveries.
20p
vioklahoma2711
19-11-2020
7
1
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MicroRNAs always function cooperatively in their regulation of gene expression. Dysfunctions of these co-functional microRNAs can play significant roles in disease development. We are interested in those multi-disease associated co-functional microRNAs that regulate their common dysfunctional target genes cooperatively in the development of multiple diseases.
17p
vioklahoma2711
19-11-2020
37
1
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Accurate gene regulatory networks can be used to explain the emergence of different phenotypes, disease mechanisms, and other biological functions. Many methods have been proposed to infer networks from gene expression data but have been hampered by problems such as low sample size, inaccurate constraints, and incomplete characterizations of regulatory dynamics.
15p
vicoachella2711
27-10-2020
19
1
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Gene Regulatory Networks (GRNs) have been previously studied by using Boolean/multi-state logics. While the gene expression values are usually scaled into the range [0, 1], these GRN inference methods apply a threshold to discretize the data, resulting in missing information.
21p
vicolorado2711
22-10-2020
7
1
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An important process for plant survival is the immune system. The induced systemic resistance (ISR) triggered by beneficial microbes is an important cost-effective defense mechanism by which plants are primed to an eventual pathogen attack.
16p
vicolorado2711
22-10-2020
13
0
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(bq) part 1 book “cancer systems biology” has contents: a roadmap of cancer systems biology, network biology, the framework of systems biology, reconstructing gene networks using gene expression profiles, from tumor genome sequencing to cancer signaling maps,… and other contents.
210p
tieu_vu15
07-09-2018
22
1
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