Literature DB >> 34530677

Cell-specific gene association network construction from single-cell RNA sequence.

Riasat Azim1, Shulin Wang1.   

Abstract

The recent development of a high throughput single-cell RNA sequence devises the opportunity to study entire transcriptomes in the smallest detail. It also leads to the characterization of molecules and subtypes of a cell. Cancer epigenetics induced not only from individual molecules but also from the dysfunction of the system and the coupling effect of genes. While rapid advances are being made in the development of tools for single-cell RNA-seq data analysis, few slants are noticed in the potential advantages of single-cell network construction.Here, we used network perturbation theory with significant analysis to develop a cell-specific network that provides an insight into gene-gene association based on molecular expressions in a single-cell resolution. Besides, using this method, we can characterize each cell by inspecting how genes are connected and can identify the hub genes using network degree theory. Pathway & Gene enrichment analysis of the identified cell-specific high network degree genes supported the effectiveness of this method. This method could be beneficial for personalized drug design and even therapeutics.

Entities:  

Keywords:  Single-cell RNA; embryonic stem cell; gene association; hub gene; perturbed network; significance analysis

Mesh:

Substances:

Year:  2021        PMID: 34530677      PMCID: PMC8794512          DOI: 10.1080/15384101.2021.1978265

Source DB:  PubMed          Journal:  Cell Cycle        ISSN: 1551-4005            Impact factor:   5.173


  55 in total

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4.  MULTIMERIN2 impairs tumor angiogenesis and growth by interfering with VEGF-A/VEGFR2 pathway.

Authors:  E Lorenzon; R Colladel; E Andreuzzi; S Marastoni; F Todaro; M Schiappacassi; G Ligresti; A Colombatti; M Mongiat
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Authors:  Romulo J C Albuquerque; Takahiko Hayashi; Won Gil Cho; Mark E Kleinman; Sami Dridi; Atsunobu Takeda; Judit Z Baffi; Kiyoshi Yamada; Hiroki Kaneko; Martha G Green; Joe Chappell; Jörg Wilting; Herbert A Weich; Satoru Yamagami; Shiro Amano; Nobuhisa Mizuki; Jonathan S Alexander; Martha L Peterson; Rolf A Brekken; Masanori Hirashima; Seema Capoor; Tomohiko Usui; Balamurali K Ambati; Jayakrishna Ambati
Journal:  Nat Med       Date:  2009-08-09       Impact factor: 53.440

Review 6.  GATA-3 promotes Th2 responses through three different mechanisms: induction of Th2 cytokine production, selective growth of Th2 cells and inhibition of Th1 cell-specific factors.

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Journal:  Cell Res       Date:  2006-01       Impact factor: 25.617

Review 7.  Single cell analysis of cancer genomes.

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Review 8.  Differential network biology.

Authors:  Trey Ideker; Nevan J Krogan
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9.  KEGG: new perspectives on genomes, pathways, diseases and drugs.

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10.  Ten hub genes associated with progression and prognosis of pancreatic carcinoma identified by co-expression analysis.

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