scholarly journals Transcriptomic data analysis and differential gene expression of antioxidant pathways in king penguin juveniles ( Aptenodytes patagonicus ) before and after acclimatization to marine life

Data in Brief ◽  
2016 ◽  
Vol 9 ◽  
pp. 549-555 ◽  
Author(s):  
Benjamin Rey ◽  
Cyril Dégletagne ◽  
Claude Duchamp
Keyword(s):  
Gene Expression ◽  
Data Analysis ◽  
Differential Gene Expression ◽  
King Penguin ◽  
Transcriptomic Data ◽  
Marine Life ◽  
Aptenodytes Patagonicus ◽  
Before And After ◽  
Differential Gene

scholarly journals Multiplicative background correction for spotted microarrays to improve reproducibility

2006 ◽  
Vol 87 (3) ◽  
pp. 195-206 ◽  
Author(s):  
DABAO ZHANG ◽  
MIN ZHANG ◽  
MARTIN T. WELLS
Keyword(s):  
Gene Expression ◽  
Data Analysis ◽  
Differential Gene Expression ◽  
Microarray Data ◽  
Background Noise ◽  
Simple Approach ◽  
Background Correction ◽  
Microarray Data Analysis ◽  
Differential Gene ◽  
Gene Expression Levels

We propose a simple approach, the multiplicative background correction, to solve a perplexing problem in spotted microarray data analysis: correcting the foreground intensities for the background noise, especially for spots with genes that are weakly expressed or not at all. The conventional approach, the additive background correction, directly subtracts the background intensities from foreground intensities. When the foreground intensities marginally dominate the background intensities, the additive background correction provides unreliable estimates of the differential gene expression levels and usually presents M–A plots with ‘fishtails’ or fans. Unreliable additive background correction makes it preferable to ignore the background noise, which may increase the number of false positives. Based on the more realistic multiplicative assumption instead of the conventional additive assumption, we propose to logarithmically transform the intensity readings before the background correction, with the logarithmic transformation symmetrizing the skewed intensity readings. This approach not only precludes the ‘fishtails’ and fans in the M–A plots, but provides highly reproducible background-corrected intensities for both strongly and weakly expressed genes. The superiority of the multiplicative background correction to the additive one as well as the no background correction is justified by publicly available self-hybridization datasets.

scholarly journals FM-test: a fuzzy-set-theory-based approach to differential gene expression data analysis

2006 ◽  
Vol 7 (Suppl 4) ◽  
pp. S7 ◽  
Author(s):  
Lily R Liang ◽  
Shiyong Lu ◽  
Xuena Wang ◽  
Yi Lu ◽  
Vinay Mandal ◽  
...  
Keyword(s):  
Gene Expression ◽  
Data Analysis ◽  
Differential Gene Expression ◽  
Set Theory ◽  
Gene Expression Data ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Expression Data ◽  
Gene Expression Data Analysis ◽  
Differential Gene

Differential Gene Expression after Emotional Freedom Techniques (EFT) Treatment: A Novel Pilot Protocol for Salivary mRNA Assessment

2016 ◽  
Vol 8 (1) ◽  
pp. 17-32
Author(s):  
Marjorie Maharaj ◽  
Keyword(s):  
Gene Expression ◽  
Differential Gene Expression ◽  
Differentially Expressed Genes ◽  
Brain Plasticity ◽  
Differentially Expressed ◽  
Control Treatment ◽  
Messenger Ribonucleic Acid ◽  
Before And After ◽  
Differential Gene ◽  
Emotional Freedom Techniques

You are here: Home › Differential Gene Expression after Emotional Freedom Techniques (EFT) Treatment: A Novel Pilot Protocol for Salivary mRNA Assessment doi 10.9769/EPJ.2016.8.1.MM Marjorie E. Maharaj, Department of Applied Psychology, Akamai University, Hilo, HI Abstract: Biopsychology is a rapidly expanding field of study since the completion of the Human Genome Project in 2003. There is little data measuring the effect of psychotherapeutic interventions on gene expression, due to the technical, logistical, and financial requirements of analysis. Being able to measure easily the effects of therapeutic experiences can validate the benefits of intervention. In order to test the feasibility of gene expression testing in a private practice setting, this study compared messenger ribonucleic acid (mRNA) and gene expression before and after psychotherapy and a control condition. With four non-clinical adult participants, it piloted a novel methodology using saliva stored at room temperature. A preliminary test of the interleukin- 8 (IL8) gene in both blood and saliva was performed in order to determine equivalency in the two biofluids; convergent validity was found. Following saliva test validation, a broad, genome-wide analysis was performed to detect differential gene expression in samples collected before and after treatment with Emotional Freedom Techniques (EFT), an evidence-based practice combining acupressure and cognitive exposure. The control treatment was non-therapeutic social interaction. To establish a baseline, participants received the control first, followed a week later by EFT. Analysis of samples was performed at three time points: immediately before treatment, immediately after, and 24 hours later. Differential expression between EFT and control was found in numerous genes implicated in overall health (p < 0.05). Further, the differentially expressed genes in this study were shown to be linked to immunity, pro or anti-inflammatory, as well as neuronal processes in the brain. Ten of the 72 differentially expressed genes are identified as promising targets for downstream research. The data show promise for the future use of salivary samples to determine the effects of therapy; this pilot protocol also illustrated the challenges and limitations of novel technologies employed in biopsychology. Keywords: epigenetics, DNA, mRNA, gene expression, protein synthesis, brain plasticity, neurogenesis, biopsychology

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