RESUMEN
MicroRNAs (miRNAs) are of significance in tuning and buffering gene expression. Despite abundant analysis tools that have been developed in the last two decades, plant miRNA identification from next-generation sequencing (NGS) data remains challenging. Here, we show that we can train a convolutional neural network to accurately identify plant miRNAs from NGS data. Based on our methods, we also present a user-friendly pure Java-based software package called Small RNA-related Intelligent and Convenient Analysis Tools (SRICATs). SRICATs encompasses all the necessary steps for plant miRNA analysis. Our results indicate that SRICATs outperforms currently popular software tools on the test data from five plant species. For non-commercial users, SRICATs is freely available at https://sourceforge.net/projects/sricats.
RESUMEN
The present study carried out a phytochemical investigation on the root barks of Dictamnus dasycarpus Turcz, leading to the isolation and characterization of two new aromatic ring butyrolactone derivatives, dasycarpusphenol acid A (1) and dasycarpusphenol acid B (2). Their structures were elucidated by using spectroscopic techniques and HR-FAB-MS. Compounds 1 and 2 exhibited antioxidant activity, with their IC50 values being 28.95 and 41.76 mg·mL-1, respectively.
