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Small non-coding RNAs (sncRNAs) are highly abundant RNAs, typically <100 nucleotides long, that act as key regulators of diverse cellular processes. Although thousands of sncRNA genes are known to exist in the human genome, no single database provides searchable, unified annotation, and expression information for full sncRNA transcripts and mature RNA products derived from these larger RNAs. Here, we present the Database of small human noncoding RNAs (DASHR). DASHR contains the most comprehensive information to date on human sncRNA genes and mature sncRNA products.

Validation of clinical biomarkers and response to therapy is a challenging topic in cancer research. An important source of information for virtual validation is the datasets generated from multi-center cancer research projects such as The Cancer Genome Atlas project (TCGA). These data enable investigation of genetic and epigenetic changes responsible for cancer onset and progression, response to cancer therapies, and discovery of the molecular profiles of various cancers.

Identifying cancer subtypes is an important component of the personalised medicine framework. An increasing number of computational methods have been developed to identify cancer subtypes. However, existing methods rarely use information from gene regulatory networks to facilitate the subtype identification. It is widely accepted that gene regulatory networks play crucial roles in understanding the mechanisms of diseases. Different cancer subtypes are likely caused by different regulatory mechanisms.

RNAi is a powerful tool for the regulation of gene expression. It is widely and successfully employed in functional studies and is now emerging as a promising therapeutic approach. Several RNAi-based clinical trials suggest encouraging results in the treatment of a variety of diseases, including cancer. Here we present miR-Synth, a computational resource for the design of synthetic microRNAs able to target multiple genes in multiple sites.