TAILIEUCHUNG - K-shell decomposition reveals structural properties of the gene coexpression network for neurodevelopment

Neurodevelopment is a dynamic and complex process, which involves interactions of thousands of genes. Understanding the mechanisms of brain development is important for uncovering the genetic architectures of neurodevelopmental disorders such as autism spectrum disorder and intellectual disability. | Turkish Journal of Biology Research Article Turk J Biol (2017) 41: 333-341 © TÜBİTAK doi: k-Shell decomposition reveals structural properties of the gene coexpression network for neurodevelopment 1,2, A. Ercüment ÇİÇEK * Department of Computer Engineering, Faculty of Engineering, Bilkent University, Ankara, Turkey 2 Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA 1 Received: Accepted/Published Online: Final Version: Abstract: Neurodevelopment is a dynamic and complex process, which involves interactions of thousands of genes. Understanding the mechanisms of brain development is important for uncovering the genetic architectures of neurodevelopmental disorders such as autism spectrum disorder and intellectual disability. The BrainSpan dataset is an important resource for studying the transcriptional mechanisms governing neurodevelopment. It contains RNA-seq and microarray data for 13 developmental periods in 8–16 brain regions. Various important studies used this dataset, in particular to generate gene coexpression networks. The topology of the BrainSpan gene coexpression network yielded various important gene clusters, which are found to play key roles in diseases. In this work, we analyze the topology of the BrainSpan gene coexpression network using the k-shell decomposition method. k-Shell decomposition is an unsupervised method to decompose a network into layers (shells) using the connectivity information and to detect a nucleus that is central to overall connectivity. Our results show that there are 267 layers in the BrainSpan gene coexpression network. The nucleus contains 2584 genes, which are related to chromatin modification function. We compared and contrasted the structure with the autonomous system level Internet. We found that despite similarities in percolation transition and crust size .

• Sinh học
• K shell decomposition
• Coexpression network
• Computational biology
• BrainSpan coexpression
• RNA seq
• BMC Bioinformatics
• Gene expression
• Next generation sequencing
• Library bias correction
• Standard RNAseq methods
• BMC Genomics
• Ribosomal RNA
• Illumina RNAseq
• Cell line samples
• Ribosomal depletion
• Genome Biology
• Single cell RNAseq
• Rare cell population composition
• Tumor heterogeneity
• Alternative splicing
• BMC Cancer
• RNAseq expression patterns
• Invasive urothelial carcinoma
• Pathologic presentation
• Molecular subtypes
• Human bladder tumors
• BMC Plant Biology
• Chromatin remodeling
• SNF2 type ATPases
• Detailed RNAseq analyses
• RNAseq analyses
• Arginine rich splicing factors
• Oryza sativa
• Robust principal component analysis
• Outlier detection
• High dimensional data
• Anomaly detection
• SL trans splicing
• De novo assembly
• RNAseq data
• Spliced Leader trans splicing
• Gene ontology
• Differential gene expression
• Sequencing messenger RNA
• RNA sequencing
• Gene expression analysis
• Read depth
• Sample number
• Matataki outperformed conventional methods
• Meta analyses
• Sequence variant
• Splicing event
• DNA mutation
• RNA editing
• High throughput RNA Sequencing
• Biologically accurate gene
• Plant Biology
• Plastid transcriptome
• Plastomic rearrangement
• Strand specific RNAseq
• Salicylic acid
• Jasmonic acid
• Web application
• Signaling pathway
• Phenotypic observation
• Collaborative cross
• Sex differences
• High fat diet
• Environmental factors
• Cell line authentication
• Cell line identification
• RNA Seq variant profiles
• Disease biology
• DNA polymorphisms
• Bioinformatics pipeline
• Black poplar
• Populus nigra
• Single Nucleotide Polymorphisms
• Primary tissue preservation without dissociation
• Hypothermic preservation
• Organ transplant preservation
• Organ transplant preservative
• Aneuploidy detection
• Single cell
• Copy number
• Hepatocellular carcinoma
• Machine learning
• Transcript expression
• Supervised cell typing
• Reference dataset construction
• Computational performance
• Single cell RNA sequencing
• In silico lineage tracing
• Neural stem cells
• Schmidtea mediterranea
• Transgenic labeling
• BMC Pulmonary Medicine
• Bronchial epithelial cells
• Hereditary COPD pathogenesis
• Non hispanic white
• Cis regulatory
• Tandem mass tag
• Parallel reaction monitoring
• Dictyostelium discoideum
• Autophagy related