imDC: an ensemble learning method for imbalanced classification with miRNA data

Wang, Chuyu; Hu, Lingling; Guo, Maozu; Liu, X.Y.; Zou, Quan

doi:10.4238/2015.january.15.15

Cited by 39 publications

(34 citation statements)

References 6 publications

(6 reference statements)

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“…Therefore, we concluded that smooth muscle cell apoptosis in coronary heart disease rats was mediated by the mitochondrial pathway. This was also in agreement with the results of previous studies (Chen et al, 2015;Femminella et al, 2015;Wang et al, 2015).…”

Section: Discussionsupporting

confidence: 83%

“…miRNA modulate various biological functions, such as cell proliferation, growth, apoptosis, and signal transduction (Chen et al, 2015;Femminella et al, 2015;Higuchi et al, 2015;Wang et al, 2015). Previous studies have also reported that miRNA-146a mediates cellular growth and proliferation in various cells (Alexandrov et al, 2014;Xie et al, 2014;Gu et al, 2015;Hill et al, 2015;Tang et al, 2015;Zhou et al, 2015), however, the role of miRNA-146a in coronary heart disease remains to be elucidated.…”

Section: Introductionmentioning

confidence: 98%

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miRNA-146a induces vascular smooth muscle cell apoptosis in a rat model of coronary heart disease via NF-κB pathway

Wu¹,

Liu²,

Wang³

et al. 2015

Genet. Mol. Res.

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ABSTRACT. The aim of this study was to investigate the role of miRNA146a in modulating the function of vascular smooth muscle cells in a rat model of coronary heart disease. Vascular smooth muscle cells were isolated and cultured from the rat coronary heart disease model and normal rats (controls). miRNA-146a levels were measured in vascular smooth muscle cells obtained from rats with coronary heart disease and control rats. The proliferation, growth, apoptosis, and activation of the NF-κB pathway in the vascular smooth muscle cells were detected using the MTT assay and flow cytometry, respectively. The role of the NF-κB pathway in modulating the apoptosis of vascular smooth muscle cells was investigated by measuring the reactivity of the cells to an NF-κB pathway inhibitor (TPCA-1). Vascular smooth muscle cells from the disease model exhibited higher levels of miRNA-146a than that by the normal controls (P = 0.0024). The vascular smooth muscle cells obtained from rats with Z.W. Wu et al. 18704©FUNPEC-RP www.funpecrp.com.br Genetics and Molecular Research 14 (4): 18703-18712 (2015) coronary heart disease showed decreased proliferation and growth and increased apoptosis. miRNA-146a overexpression elevated the rate of cell apoptosis. The NF-κB pathway was activated in vascular smooth muscle cells obtained from rats with coronary heart disease. Inhibition of the NF-κB pathway significantly decreased the rate of vascular smooth muscle cell apoptosis in coronary heart disease rats (P = 0.0038). In conclusion, miRNA146a was found to induce vascular smooth muscle cell apoptosis in rats with coronary heart disease via the activation of the NF-κB signal pathway.

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Section: Discussionsupporting

confidence: 83%

Section: Introductionmentioning

confidence: 98%

miRNA-146a induces vascular smooth muscle cell apoptosis in a rat model of coronary heart disease via NF-κB pathway

Wu¹,

Liu²,

Wang³

et al. 2015

Genet. Mol. Res.

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“…In our future work, we will try other features considering long range sequence information, which is indicted to be useful for the enhancer classification in our current work. We will also try the imbalanced classifiers [52][53][54][55][56]on our dataset, which has been employed CD-HIT and random sampling strategy for the large negative data. Combined with some more sophisticated machine learning models and feature reduction methods [57], we anticipate better performance can be achieved.…”

Section: Resultsmentioning

confidence: 99%

iEnhancer-PsedeKNC: Identification of enhancers and their subgroups based on Pseudo degenerate kmer nucleotide composition

Liu

2016

Neurocomputing

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“…However, this metric might unsuitable to measure the performance of imbalanced class distribution. Hence, additional metrics like precision, recall, F-measure were used (Wang et al, 2015;Zhang et al, 2015). The experiment was done under two conditions; using all extracted features (FS1) and using reduced features (FS2).…”

Section: Resultsmentioning

confidence: 99%

Recognizing Complex Human Activities using Hybrid Feature Selections based on an Accelerometer Sensor

Zainudin¹,

Sulaiman²,

Mustapha³

et al. 2017

IJTech

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Wearable sensor technology is evolving in parallel with the demand for human activity monitoring applications. According to World Health Organization (WHO), the percentage of health problems occurring in the world population, such as diabetes, heart problem, and high blood pressure rapidly increases from year-to-year. Hence, regular exercise, at least twice a week, is encouraged for everyone, especially for adults and the elderly. An accelerometer sensor is preferable, due to privacy concerns and the low cost of installation. It is embedded within smartphones to monitor the amount of physical activity performed. One of the limitations of the various classifications is to deal with the large dimension of the feature space. Practically speaking, a large amount of memory space is demanded along with high processor performance to process a large number of features. Hence, the dimension of the features is required to be minimized by selecting the most relevant feature before it is classified. In order to tackle this issue, the hybrid feature selection using Relief-f and differential evolution is proposed. The public domain activity dataset from Physical Activity for Ageing People (PAMAP2) is used in the experimentation to identify the quality of the proposed method. Our experimental results show outstanding performance to recognize different types of physical activities with a minimum number of features. Subsequently, our findings indicate that the wrist is the best sensor placement to recognize the different types of human activity. The performance of our work also been compared with several state-of-the-art of features for selection algorithms.

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imDC: an ensemble learning method for imbalanced classification with miRNA data

Cited by 39 publications

References 6 publications

miRNA-146a induces vascular smooth muscle cell apoptosis in a rat model of coronary heart disease via NF-κB pathway

miRNA-146a induces vascular smooth muscle cell apoptosis in a rat model of coronary heart disease via NF-κB pathway

iEnhancer-PsedeKNC: Identification of enhancers and their subgroups based on Pseudo degenerate kmer nucleotide composition

Recognizing Complex Human Activities using Hybrid Feature Selections based on an Accelerometer Sensor

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