A lncRNA-disease association prediction model based on the two-step PU learning and fully connected neural networks.

Long non-coding RNAs (lncRNAs) have been shown to play a regulatory role in various processes of human diseases. However, lncRNA experiments are inefficient, time-consuming and highly subjective, so that the number of experimentally verified associations between lncRNA and diseases is limited. In the era of big data, numerous machine learning methods have been proposed to predict the potential association between lncRNA and diseases, but the characteristics of the associated data were seldom explored.

The complete chloroplast genome of .

is a valuable hard wood species in southern China. In this study, we sequenced, assembled and annotated the complete chloroplast genome of . The complete cp genome of was 159,352 bp in length, with a total of 109 unique annotated genes, including 78 protein-coding genes, 27 tRNA genes and 4 rRNA genes.

Lectotypification of the name f. and its taxonomic status.

A nomenclatural and taxonomic treatment of the name Melastoma candidum f. albiflorum (Melastomataceae) is presented. A lectotype is designated for this name, with an updated morphological description based on fresh material.

Molecular identification of natural hybridization between and in Sarawak, Malaysia.

Hybridization is very common in flowering plants and it plays a significant role in plant evolution and adaptation. L. (Melastomataceae) comprises about 80-90 species in tropical Asia and Oceania, among which 41 species occur in Borneo.