RESUMEN
CpG islands are generally known as the epigenetic regulatory regions in accordance with histone modifications, methylation, and promoter activity. There is a significant need for the exact mapping of DNA methylation in CpG islands to understand the diverse biological functions. However, the precise identification of CpG islands from the whole genome through experimental and computational approaches is still challenging. Numerous computational methods are being developed to detect the CpG-enriched regions, effectively, to reduce the time and cost of the experiments. Here, we review some of the latest computational CpG detection methods that utilize clustering, patterns and physical-distance like parameters for CpG island detection. The comparative analyses of the methods relying on different principles and parameters allow prioritizing the algorithms for specific CpG associated datasets to achieve higher accuracy and sensitivity. A number of computational tools based on the window, Hidden Markov Model, density and distance-/length-based algorithms are being applied on human or mammalian genomes for accurate CpG detection. Comparative analyses of CpG island detection algorithms facilitate to prefer the method according to the target genome and required parameters to attain higher accuracy, specificity, and performance. There is still a need for efficient computational CpG detection methods with lower false-positive results. This review provides a better understanding about the principles of tools that will assist to prioritize and develop the algorithms for accurate CpG islands detection.
Asunto(s)
Biología Computacional , Islas de CpG/genética , Metilación de ADN/genética , Algoritmos , Análisis por Conglomerados , Genoma Humano/genética , Humanos , Secuencias Reguladoras de Ácidos Nucleicos/genéticaRESUMEN
Circadian rhythms of heart rate variability have been widely studied in recent years. However, most previous reports described such rhythms in terms of normalized units of the low- and high-frequency (LF and HF) spectral components. In this study, we analyzed circadian rhythms of spectral components in absolute units and found unexpected results in normal subjects as well as coronary heart disease (CHD) and congestive heart failure (CHF) patient groups. The results indicate that the notion of sympathovagal balance needs to be re-evaluated.
Asunto(s)
Ritmo Circadiano/fisiología , Enfermedad Coronaria/fisiopatología , Frecuencia Cardíaca/fisiología , Sistema Nervioso Simpático/fisiología , Humanos , Sistema Nervioso Simpático/fisiopatologíaRESUMEN
A recirculatory physiological model of the determinants of the myocardial concentrations of lignocaine after intravenous administration was developed in sheep and validated with the intention of analysing and predicting the outcome of altered dose regimens and various pathophysiological states on the initial myocardial concentrations of lignocaine. The structure and parameters of the model were determined by hybrid modelling of the time-courses of the pulmonary artery, arterial and coronary sinus concentrations of lignocaine after the intravenous administration of 100 mg of lignocaine over 5 min to 5 chronically instrumented sheep. The model accounted for the determinants of the myocardial concentrations via compartments for venous mixing, the lung (a single-compartment model with a first-order loss) and the heart (a single flow-limited compartment). Recirculation and the remainder of the body were represented as a single tissue pool with a clearance term. The distribution volume of the heart was 0.42+/-0.009 L, which gave a half-time of myocardium:blood equilibration of 2.37 min. The distribution volume of the lungs was 5.40+/-0.23 L, with an apparent first-order loss of 1.02 L min(-1) representing deep distribution or metabolism. The validity of the model was tested by comparing the predictions of the model with the equivalent data collected in 6 sheep when lignocaine (89 mg) was administered via a complex dose regimen with a faster initial rate of infusion (39.1 mg min(-1)), declining exponentially to basal infusion rate (7.02 mg min(-1)) over 8 min. The predictions of the model were in general agreement with these data. It is concluded that the model was sufficient to account for the effect of altered dose regimens of lignocaine on the time-course of its myocardial concentrations.