Rice

The computational identification of non-coding RNA regions on the genome is currently receiving much attention. However, it is essentially harder than gene-finding problems for protein-coding regions because non-coding RNA sequences do not have strong statistical signals. Since comparative sequence analysis is effective for non-coding RNA detection, efficient computational methods are expected for structural alignment of RNA sequences.

Studies from flies and insects have reported the existence of a special class of miRNA, called mirtrons that are produced from spliced-out introns in a DROSHA-independent manner. The spliced-out lariat is debranched and refolded into a stem-loop structure resembling the pre-miRNA, which can then be processed by DICER into mature ~21 nt species. The mirtrons have not been reported from plants. In this study, we present MirtronPred, a web based server to predict mirtrons from intronic sequences.

In plants, various phloem-mobile macromolecules including noncoding RNAs, mRNAs and proteins are suggested to act as important long-distance signals in regulating crucial physiological and morphological transition processes such as flowering, plant growth and stress responses. Given recent advances in high-throughput sequencing technologies, numerous mobile macromolecules have been identified in diverse plant species from different plant families.

CePa is an R package aiming to find significant pathways through network topology information. The package has several advantages compared with current pathway enrichment tools. First, pathway node instead of single gene is taken as the basic unit when analysing networks to meet the fact that genes must be constructed into complexes to hold normal functions. Second, multiple network centralities are applied simultaneously to measure importance of nodes from different aspects to make a full view on the biological system.