scholarly journals Comprehensive Expression Profiling and Functional Network Analysis of Porphyra-334, One Mycosporine-Like Amino Acid (MAA), in Human Keratinocyte Exposed with UV-radiation

Marine Drugs ◽  
2017 ◽  
Vol 15 (7) ◽  
pp. 196 ◽  
Author(s):  
Sung-Suk Suh ◽  
Sung Lee ◽  
Ui Youn ◽  
Se Han ◽  
Il-Chan Kim ◽  
...  
Keyword(s):  
Amino Acid ◽  
Network Analysis ◽  
Uv Radiation ◽  
Expression Profiling ◽  
Functional Network ◽  
Human Keratinocyte

1571 GENE EXPRESSION PROFILING AND FUNCTIONAL NETWORK ANALYSIS OF BENIGN PROSTATIC HYPERPLASIA MODEL RAT

2012 ◽  
Vol 187 (4S) ◽  
Author(s):  
Yoshiyuki Kojima ◽  
Shoichi Sasaki ◽  
Makoto Imura ◽  
Kentaro Mizuno ◽  
Atsushi Okada ◽  
...  
Keyword(s):  
Gene Expression ◽  
Benign Prostatic Hyperplasia ◽  
Network Analysis ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Prostatic Hyperplasia ◽  
Functional Network

scholarly journals Comprehensive Expression Profiling and Functional Network Analysis of p53-Regulated MicroRNAs in HepG2 Cells Treated with Doxorubicin

PLoS ONE ◽  
2016 ◽  
Vol 11 (2) ◽  
pp. e0149227 ◽  
Author(s):  
Yalan Yang ◽  
Wenrong Liu ◽  
Ruofan Ding ◽  
Lili Xiong ◽  
Rongkun Dou ◽  
...  
Keyword(s):  
Network Analysis ◽  
Expression Profiling ◽  
Hepg2 Cells ◽  
Functional Network

scholarly journals Functional Network Analysis Reveals Extended Gliomagenesis Pathway Maps and Three Novel MYC-Interacting Genes in Human Gliomas

2005 ◽  
Vol 65 (19) ◽  
pp. 8679-8689 ◽  
Author(s):  
Markus Bredel ◽  
Claudia Bredel ◽  
Dejan Juric ◽  
Griffith R. Harsh ◽  
Hannes Vogel ◽  
...  
Keyword(s):  
Network Analysis ◽  
Functional Network ◽  
Human Gliomas

CNTM-06. Individual Cerebrocerebellar Functional Network Analysis for Decoding the Symptomatological Dynamics of Posterior Fossa Syndrome

2021 ◽  
Vol 23 (Supplement_6) ◽  
pp. vi225-vi225
Author(s):  
Ko-Ting Chen ◽  
Sheng-Yao Huang
Keyword(s):  
Network Analysis ◽  
Posterior Fossa ◽  
Clinical Neurophysiology ◽  
Clinical Symptoms ◽  
Critical Role ◽  
Functional Network ◽  
Posterior Fossa Syndrome ◽  
Structural Abnormalities ◽  
Common Pathogenesis

Abstract Posterior fossa syndrome (PFS) consists of three types of symptom (motoric, linguistic, and neurobehavioral) in patients with posterior fossa pathologies. The evolutional mechanism of this high cognitive syndromic complex from cerebellar origin remains unconfirmed. Previous studies analyzing PFS patients mostly focused on the association between structural abnormalities that occur during PFS, of which proximal efferent cerebellar pathway (pECP) injury appears to be the most common pathogenesis. However, structural imaging may not be sensitive enough to determine the dynamic course of PFS, since the symptomatology is primarily an output of cerebral operation. On the other hand, a network neuroscience approach using a mathematical model to extract information from functional imaging to generate interregional connectivity provides abundant evidence that the cerebellum is influential in modulating cerebral functions. This study applied a network approach to children with PFS. Scaling of each symptom domain was used to quantify the dynamics of the syndrome. An individual cerebrocerebellar functional network analysis was then performed to determine the network dynamics during PFS. Cross-validation of clinical neurophysiology and functional neuroscience suggested the critical role of the pECP within PFS from the network analysis. The employed approach was therefore useful in determining the complex clinical symptoms using individual functional network analysis, which bridges the gap between structural neuroimaging and clinical neurophysiology.

scholarly journals Co-expression networks for plant biology: why and how

2019 ◽  
Vol 51 (10) ◽  
pp. 981-988 ◽  
Author(s):  
Xiaolan Rao ◽  
Richard A Dixon
Keyword(s):  
Gene Expression ◽  
Network Analysis ◽  
Expression Analysis ◽  
Expression Profiling ◽  
Recent Literature ◽  
Genomic Data ◽  
Relevant Information ◽  
Plant Biology ◽  
Biologically Relevant

Abstract Co-expression network analysis is one of the most powerful approaches for interpretation of large transcriptomic datasets. It enables characterization of modules of co-expressed genes that may share biological functional linkages. Such networks provide an initial way to explore functional associations from gene expression profiling and can be applied to various aspects of plant biology. This review presents the applications of co-expression network analysis in plant biology and addresses optimized strategies from the recent literature for performing co-expression analysis on plant biological systems. Additionally, we describe the combined interpretation of co-expression analysis with other genomic data to enhance the generation of biologically relevant information.

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