Iridescence is an original type of colouration that is relatively widespread in nature but has been either incompletely described or entirely neglected in prokaryotes. Recently, we reported a brilliant 'pointillistic' iridescence in agar-grown colony...
False-positive assay readouts caused by badly behaving compounds-frequent hitters, pan-assay interference compounds (PAINS), aggregators, and others-continue to pose a major challenge to experimental screening. There are only a few in silico methods ...
Synapse formation analyses can be performed by imaging and quantifying fluorescent signals of synaptic markers. Traditionally, these analyses are done using simple or multiple thresholding and segmentation approaches or by labor-intensive manual anal...
The detection of uracil-DNA glycosylase (UDG) activity is pivotal for its biochemical studies and the development of drugs for UDG-related diseases. Here, we explored an integrated DNA structure switch for high sensitive detection of UDG activity. Th...
Proteomics data analysis based on the mass-spectrometry technique can provide a powerful tool for early diagnosis of tumors and other diseases. It can be used for exploring the features that reflect the difference between samples from high-throughput...
Accurately predicting cardioactive effects of new molecular entities for therapeutics remains a daunting challenge. Immense research effort has been focused toward creating new screening platforms that utilize human pluripotent stem cell (hPSC)-deriv...
The synthesis of glycans and the sorting of proteins are critical functions of the Golgi apparatus and depend on its highly complex and compartmentalized architecture. High-content image analysis coupled to RNA interference screening offers opportuni...
In the last decade, high-content screening based on multivariate single-cell imaging has been proven effective in drug discovery to evaluate drug-induced phenotypic variations. Unfortunately, this method inherently requires fluorescent labeling which...
Testing potential drug treatments in animal disease models is a decisive step of all preclinical drug discovery programs. Yet, despite the importance of such experiments for translational medicine, there have been relatively few efforts to comprehens...
We aimed to identify optimal machine-learning methods for radiomics-based prediction of local failure and distant failure in advanced nasopharyngeal carcinoma (NPC). We enrolled 110 patients with advanced NPC. A total of 970 radiomic features were ex...