AIpollen: An Analytic Website for Pollen Identification Through Convolutional Neural Networks.

With the rapid development of artificial intelligence, deep learning has been widely applied to complex tasks such as computer vision and natural language processing, demonstrating its outstanding performance. This study aims to exploit the high precision and efficiency of deep learning to develop a system for the identification of pollen. To this end, we constructed a dataset across 36 distinct genera.

Impact of Chromosomal Fusion and Transposable Elements on the Genomic Evolution and Genetic Diversity of Species.

The genus belongs to the sole family and is the single genus within the order Aquifoliales, exhibiting significant phenotypic diversity. However, the genetic differences underlying these phenotypic variations have rarely been studied. In this study, collinearity analyses of three genomes, Thunb.

Species-Specific miRNAs Contribute to the Divergence between Deciduous and Evergreen Species in .

MicroRNAs (miRNAs) are pivotal regulators of gene expression, playing crucial roles in plant developmental processes and environmental responses. However, the function of miRNAs in influencing deciduous traits has been little explored. Here, we utilized sRNA-seq on two deciduous species, (Hand.

Programmed cell death in wheat during starchy endosperm development.

The starchy endosperm of wheat underwent programmed cell death (PCD) during its development. It showed a ladder of DNA fragments in multiples of 180-200 bp at specific stages when analyzed by agarose gel electrophoresis. The onset of internucleosomal fragmentation of the genome in wheat endosperm could be accelerated by ethylene.