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Meta-Analysis of RNA-Seq and Microarray Expression Data to Identify Genes Effective in Sheep Muscle Growth and Development [PDF]
پژوهشهای علوم دامی ایران, 2023 Introduction: Among different sheep breeds in the world, the Texel breed is known as a meaty and muscular breed. Skeletal muscle growth is a step-by-step and exponential process from differentiation, development and maturation, which is regulated by gene
Fahime Mohammadi +2 more
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Characterization of RNA in exosomes secreted by human breast cancer cell lines using next-generation sequencing [PDF]
PeerJ, 2013 Exosomes are nanosized (30–100 nm) membrane vesicles secreted by most cell types. Exosomes have been found to contain various RNA species including miRNA, mRNA and long non-protein coding RNAs. A number of cancer cells produce elevated levels of exosomes.
Piroon Jenjaroenpun +5 more
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Identifying gene interaction enrichment for gene expression data. [PDF]
PLoS ONE, 2009 Gene set analysis allows the inclusion of knowledge from established gene sets, such as gene pathways, and potentially improves the power of detecting differentially expressed genes.
Jigang Zhang, Jian Li, Hong-Wen Deng
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Implementing Gene Expression Programming in the Parallel Environment for Big Datasets’ Classification [PDF]
Vietnam Journal of Computer Science, 2019 The paper investigates a Gene Expression Programming (GEP)-based ensemble classifier constructed using the stacked generalization concept. The classifier has been implemented with a view to enable parallel processing with the use of Spark and SWIM — an ...
Joanna Jȩdrzejowicz +2 more
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The GENDULF algorithm: mining transcriptomics to uncover modifier genes for monogenic diseases
Molecular Systems Biology, 2020 Modifier genes are believed to account for the clinical variability observed in many Mendelian disorders, but their identification remains challenging due to the limited availability of genomics data from large patient cohorts.
Noam Auslander +7 more
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BMC Genomics, 2017 Background High-grade serous ovarian carcinoma (HG-SOC) is the dominant tumor histologic type in epithelial ovarian cancers, exhibiting highly aberrant microRNA expression profiles and diverse pathways that collectively determine the disease ...
Vladimir A. Kuznetsov +2 more
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Seed-based biclustering of gene expression data. [PDF]
PLoS ONE, 2012 BACKGROUND: Accumulated biological research outcomes show that biological functions do not depend on individual genes, but on complex gene networks. Microarray data are widely used to cluster genes according to their expression levels across experimental
Jiyuan An +2 more
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Time-Course Gene Set Analysis for Longitudinal Gene Expression Data. [PDF]
PLoS Computational Biology, 2015 Gene set analysis methods, which consider predefined groups of genes in the analysis of genomic data, have been successfully applied for analyzing gene expression data in cross-sectional studies.
Boris P Hejblum +2 more
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Interactive Analysis, Exploration, and Visualization of RNA-Seq Data with SeqCVIBE
Methods and Protocols, 2022 The rise of modern gene expression profiling techniques, such as RNA-Seq, has generated a wealth of high-quality datasets spanning all fields of current biological research.
Efthimios Bothos +2 more
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BMC Bioinformatics, 2017 Background sgnesR (Stochastic Gene Network Expression Simulator in R) is an R package that provides an interface to simulate gene expression data from a given gene network using the stochastic simulation algorithm (SSA).
Shailesh Tripathi +5 more
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