scholarly journals Integrated analysis of exosomal lncRNA and mRNA expression profiles reveals the involvement of lnc‐MKRN2‐42:1 in the pathogenesis of Parkinson's disease

2019 ◽  
Vol 26 (5) ◽  
pp. 527-537
Author(s):  
Qiao Wang ◽  
Chun‐Lei Han ◽  
Kai‐Liang Wang ◽  
Yun‐Peng Sui ◽  
Zhi‐Bao Li ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Mrna Expression ◽  
Expression Profiles ◽  
Integrated Analysis

scholarly journals Mining genetic and transcriptomic data using machine learning approaches in Parkinson’s disease

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Chang Su ◽  
Jie Tong ◽  
Fei Wang
Keyword(s):  
Machine Learning ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Data Analysis ◽  
Expression Profiles ◽  
Relevant Literature ◽  
Integrated Analysis ◽  
Learning Models ◽  
Transcriptomic Data ◽  
Machine Learning Models

Abstract High-throughput techniques have generated abundant genetic and transcriptomic data of Parkinson’s disease (PD) patients but data analysis approaches such as traditional statistical methods have not provided much in the way of insightful integrated analysis or interpretation of the data. As an advanced computational approach, machine learning, which enables people to identify complex patterns and insight from data, has consequently been harnessed to analyze and interpret large, highly complex genetic and transcriptomic data toward a better understanding of PD. In particular, machine learning models have been developed to integrate patient genotype data alone or combined with demographic, clinical, neuroimaging, and other information, for PD outcome study. They have also been used to identify biomarkers of PD based on transcriptomic data, e.g., gene expression profiles from microarrays. This study overviews the relevant literature on using machine learning models for genetic and transcriptomic data analysis in PD, points out remaining challenges, and suggests future directions accordingly. Undoubtedly, the use of machine learning is amplifying PD genetic and transcriptomic achievements for accelerating the study of PD. Existing studies have demonstrated the great potential of machine learning in discovering hidden patterns within genetic or transcriptomic information and thus revealing clues underpinning pathology and pathogenesis. Moving forward, by addressing the remaining challenges, machine learning may advance our ability to precisely diagnose, prognose, and treat PD.

Integrated analysis of non-coding RNA and mRNA expression profiles of 2 pig breeds differing in muscle traits

2017 ◽  
Vol 95 (3) ◽  
pp. 1092 ◽  
Author(s):  
J. Sun ◽  
M. Xie ◽  
Z. Huang ◽  
H. Li ◽  
T. chen ◽  
...  
Keyword(s):  
Mrna Expression ◽  
Expression Profiles ◽  
Integrated Analysis ◽  
Pig Breeds ◽  
Non Coding Rna

scholarly journals Integrated analysis of miRNA and mRNA expression profiles in tilapia gonads at an early stage of sex differentiation

BMC Genomics ◽  
2016 ◽  
Vol 17 (1) ◽  
Author(s):  
Wenjing Tao ◽  
Lina Sun ◽  
Hongjuan Shi ◽  
Yunying Cheng ◽  
Dongneng Jiang ◽  
...  
Keyword(s):  
Mrna Expression ◽  
Early Stage ◽  
Expression Profiles ◽  
Sex Differentiation ◽  
Integrated Analysis

scholarly journals Integrated analysis of microRNA and mRNA expression profiles in abdominal adipose tissues in chickens

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
H. Y. Huang ◽  
R. R. Liu ◽  
G. P. Zhao ◽  
Q.H. Li ◽  
M. Q. Zheng ◽  
...  
Keyword(s):  
Mrna Expression ◽  
Expression Profiles ◽  
Integrated Analysis ◽  
Adipose Tissues

scholarly journals Integrated analysis of microRNA and mRNA expression profiles in splenomegaly induced by non-cirrhotic portal hypertension in rats

2018 ◽  
Vol 8 (1) ◽  
Author(s):  
Junji Saruwatari ◽  
Chao Dong ◽  
Teruo Utsumi ◽  
Masatake Tanaka ◽  
Matthew McConnell ◽  
...  
Keyword(s):  
Portal Hypertension ◽  
Mrna Expression ◽  
Expression Profiles ◽  
Integrated Analysis

Integrated Analysis of MicroRNA and mRNA Expression Profiles in Rheumatoid Arthritis Synovial Monocytes

2011 ◽  
Vol 18 (4) ◽  
pp. 253 ◽  
Author(s):  
Jong Dae Ji ◽  
Tae-Hwan Kim ◽  
Bitnara Lee ◽  
Kyung-Sun Na ◽  
Sung Jae Choi ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Mrna Expression ◽  
Expression Profiles ◽  
Integrated Analysis ◽  
Synovial Monocytes
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