MiRNAs have been widely studied due to their important post-transcriptional regulatory roles in gene expression. Many reports have demonstrated the evidence of miRNA isoform products (isomiRs) in high-throughput small RNA sequencing data. However, the biological function involved in these molecules is still not well investigated. Here, we developed a Shannon entropy-based model to estimate isom...

Signal detection performance in cognitive radio architecture is enhanced by the cooperation of sensing detectors if the fading and shadowing effects exist on the channel. A cooperative spectrum sensing technique in cognitive radio networks based on two-sample Kolmogorov-Smirnov test is proposed in this paper and proposed sensing scheme is examined under Rician fading channel. The performance of...

Background: We aimed to establish a novel diagnostic model for kidney diseases by combining artificial intelligence with complete mass spectrum information from urinary proteomics. Methods: enrolled 134 patients (IgA nephropathy, membranous and diabetic disease) 68 healthy participants as controls, total of 610,102 spectra their proteomic profiles. The training data set (80%) was used create us...

We show that as many as 4000 SNeIa may be required to detect the effect of weak lensing on their flux distribution with a high level of significance. However, if the intrinsic SNeIa magnitude dispersion is unknown one needs an even higher number of SNeIa (an order of magnitude more) to reach a similar level of statistical significance. Moreover, the ability to separate the lensing contribution ...

Spectrum sensing, in particular, detecting the presence of licensed or incumbent users in licensed spectrum, is one of the pivotal tasks in cognitive radio network. In this paper, we tackle the spectrum sensing problem by using statistical test theory and derive novel spectrum sensing approaches. We apply the classical Kolmogorov-Smirnov (KS) test under the assumption that the noise probability...

BACKGROUND The model-based dynamic insulin sensitivity and secretion test (DISST) uses fasting glucose (G 0 ) as the basal glucose (G B ) concentration when assessing insulin sensitivity (SI). However, this model was developed in a healthy, normoglycaemic cohort. We sought to determine the suitability the DISST model has for individuals with established type 2 diabetes (T2D). METHODS 14 parti...

The algorithm takes as input a vector of data values which contains an initial segment of noise followed by the arrival of a signal. The algorithm returns an estimate of the time of arrival of the signal along with a binary random variable conf indicating the credibility of the estimate: conf = 1 indicating a level of confidence, conf = 0 indicating no confidence in the estimate. For the purpos...

A new two-dimensional version of the Kolmorogov-Smirnov test has been developed for the testing of data which has been placed in a two-dimensional array of bins. Monte Carlo testing has been used to derive the test statistics for 8 x 8, 16 x 16 and 32 x 32 arrays. The predicted probabilities for non-square arrays and arrays with intermediate numbers of elements are compared to the probabilities...

BACKGROUND Influenza is a well known and common human respiratory infection, causing significant morbidity and mortality every year. Despite Influenza variability, fast and reliable outbreak detection is required for health resource planning. Clinical health records, as published by the Diagnosticat database in Catalonia, host useful data for probabilistic detection of influenza outbreaks. ME...