The molecular structure of macromolecules in living cells is ambiguous unless we classify them in a scientific manner. Signal peptides are of vital importance in determining the behavior of newly formed proteins towards their destined path in cellular and extracellular location in both eukaryotes and prokaryotes. In the present research work, a novel method is offered to foreknow the behavior of signal peptides and determine their cleavage site. The proposed model employs neural networks using isolated sets of prokaryote and eukaryote primary sequences. Protein sequences are classified as secretory or non-secretory in order to investigate secretory proteins and their signal peptides. In comparison with the previous prediction tools, the proposed algorithm is more rigorous, well-organized, significantly appropriate and highly accurate for the examination of signal peptides even in extensive collection of protein sequences.
Background: In various biological processes and cell functions, Post Translational Modifications (PTMs) bear critical significance. Hydroxylation of proline residue is one kind of PTM, which occurs following protein synthesis. The experimental determination of hydroxyproline sites in an uncharacterized protein sequence requires extensive, time-consuming and expensive tests. Methods: With the torrential slide of protein sequences produced in the post-genomic age, certain remarkable computational strategies are desired to overwhelm the issue. Keeping in view the composition and sequence order effect within polypeptide chains, an innovative in-silico predictor via a mathematical model is proposed. Results: Later, it was stringently verified using self-consistency, cross-validation and jackknife tests on benchmark datasets. It was established after a rigorous jackknife test that the new predictor values are superior to the values predicted by previous methodologies. Conclusion: This new mathematical technique is the most appropriate and encouraging as compared with the existing models.
Introduction: Hydroxylation is one of the most important post-translational modification (PTM) in cellular functions and is linked to various diseases. The addition of one of a hydroxyl group (OH) to the lysine sites produce hydroxylysine when undergoes chemical modification. Methods: The method which is used in this study for identifying hydroxylysine sites based on powerful mathematical and statistical methodology incorporating sequence-order effect and composition of each object within protein sequences. This predictor is called "iHyd-LysSite (EPSV)" (identifying hydroxylysine sites by extracting enhanced position and sequence variant technique). The prediction of hydroxylysine sites by experimental methods are difficult, laborious and highly expensive. In silico technique is an alternative approach to identify hydroxylysine sites in proteins. Results: The experimental results require that the predictive model should have high sensitivity and specificity values and must be more accurate. The self-consistency, independent, 10-fold cross-validation and jackknife tests are performed for validation purpose. These tests are resulted by using three renowned classifiers, neural networks (NN), random forest (RF) and support vector machine (SVM) with the demanding prediction rate. The overall predictive outcomes are extraordinarily superior than the results obtained by previous predictors. The proposed model contributed excellent prediction rate in the system for NN, RF, and SVM classifiers. The sensitivity and specificity results using all these classifiers for jackknife test are and . Conclusion: The results obtained by the proposed tool show that this method may meet the future demand of hydroxylysine sites with a better prediction rate over the existing methods.
Environmental applications of composites have attracted the interests of researchers due to their excellent adsorption efficiency for pollutants. Native, HCl pre-treated clay and MnFe2O4/clay composite were investigated as an adsorbent for removal of methyl green from aqueous solution. The adsorption behaviors of dye onto native, HCl pre-treated and composite clays were studied as a function of contact time, adsorbent dose, pH, initial dye concentration and temperature. Maximum dye adsorption of 44 mg/g was achieved at pH of 8, contact time 40 min, adsorbent dose 0.20 g/L and initial dye concentration of 125 mg/L using clay composite. The Langmuir isotherm and pseudo-second-order kinetic model best explained the methyl green dye adsorption onto clay adsorbents. Thermodynamic parameters revealed the endothermic and spontaneous adsorption nature of dye. From results, it is concluded that clay has potential for adsorbing methyl green and can be used for the removal of dyes from industrial effluents.
Crime committed by a woman is an important factor that influences the family’s harmony and social stability. In recent years, the female crime rate has been a gradual increase, and its growth rate has exceeded that of male crime in the corresponding period. This not only relates to the weakly legal consciousness of a small number of women but also relates with the families and the society. To effectively prevent and control female crime. Efforts should be made to enhance women's legal and moral education, combat domestic violence, perfect the legal system, improve the social security system, and strengthen the assistance and education to female prisoners. This study is designed to investigate the psychological and health issues faced by women who are under lock in the district jail Faisalabad. The study was qualitative and the case study method was used for data collection from the district jail Faisalabad. The present study was conducted in the district jail of Faisalabad. 15 Women were taken as a sample size that is under lock in the district jail Faisalabad. In-depth interviews were conducted with the respondents, to explore their psychological and health issues. Moreover, thematic analysis was applied to draw the results and analysis. Keywords: Psychological, health, women, family’s harmony, preventing measures, thematic analysis
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