Enhancers are DNA fragments that do not encode RNA molecules and proteins, but they act critically in the production of RNAs and proteins by controlling gene expression. Prediction of enhancers and their strength plays significant role in regulating gene expression. Prediction of enhancer regions, in sequences of DNA, is considered a difficult task due to the fact that they are not close to the target gene, have less common motifs and are mostly tissue/cell specific. In recent past, several bioinformatics tools were developed to discriminate enhancers from other regulatory elements and to identify their strengths as well. However the need for improvement in the quality of its prediction method requires enhancements in its application value practically. In this study, we proposed a new method that builds on nucleotide composition and statistical moment based features to distinguish between enhancers and non-enhancers and additionally determine their strength. Our proposed method achieved accuracy better than current state-of-the-art methods using 5-fold and 10-fold cross-validation. The outcomes from our proposed method suggest that the use of statistical moments based features could bear more efficient and effective results. For the accessibility of the scientific community, we have developed a user-friendly web server for EnhancerP-2L which will increase the impact of bioinformatics on medicinal chemistry and drive medical science into an unprecedented resolution. Web server is freely accessible at http://www.biopred.org/enpred .

Nanoparticles are generally used to scatter and absorb solar radiations in nanofluid-based direct solar receivers to efficiently transport and store the heat. However, solar energy absorption in nanofluid can be enhanced by using differential materials and tuning nanofluid parameter. In this regard, theoretical investigations of unsteady homogeneous Hiemenz flow of an incompressible nanofluid having copper and silver nanoparticles over a porous wedge is carried out by using optimal homotopy asymptotic method (OHAM). Hence, a semi-analytical solver is applied to the transformed system to study the significance of magnetic field along with Prandtl number. In this work, impacts of conductive radiations, heat sink/source, unsteadiness, and flow parameters have been investigated for velocity and temperature profiles of copper and silver nanoparticles-based nanofluid. The effects of magnetic strength, volume fraction of nanoparticles, thermal conductivity, and flow parameters have also been studied on the considered nanofluids.