An immunochromatographic test system was developed for the detection of T-2 toxin (T2T), which is one of priority contaminants of cereals. The detection is based on the competition between T2T in the sample and the T2T-protein conjugate immobilized o...
Characterizing the binding behaviors of RNA-binding proteins (RBPs) is important for understanding their functional roles in gene expression regulation. However, current high-throughput experimental methods for identifying RBP targets, such as CLIP-s...
Quantitative evaluation of binding affinity changes upon mutations is crucial for protein engineering and drug design. Machine learning-based methods are gaining increasing momentum in this field. Due to the limited number of experimental data, using...
Despite the increasing use of high-throughput experiments in molecular biology, methods for evaluating and classifying the acquired results have not kept pace, requiring significant manual efforts to do so. Here, we present CiRCus, a framework to gen...
Chitosan-based hybrid hydrogels such as chitosan hydrogel (CH), chitosan hydrogel with activated carbon (CH-AC), scaffold-chitosan hydrogel (SCH), scaffold-chitosan hydrogel with activated carbon (SCH-AC) and scaffold-chitosan hydrogel with carbon na...
Gaining insight into the pharmacology of ligand engagement with G-protein coupled receptors (GPCRs) under biologically relevant conditions is vital to both drug discovery and basic research. NanoLuc-based bioluminescence resonance energy transfer (Na...
Molecular descriptors are essential to not only quantitative structure activity/property relationship (QSAR/QSPR) models, but also machine learning based chemical and biological data analysis. In this paper, we propose persistent spectral hypergraph ...