MOTIVATION: Gene lists are routinely produced from various omic studies. Enrichment analysis can link these gene lists with underlying molecular pathways and functional categories such as gene ontology (GO) and other databases. RESULTS: To complement existing tools, we developed ShinyGO based on a large annotation database derived from Ensembl and STRING-db for 59 plant, 256 animal, 115 archeal and 1678 bacterial species. ShinyGO's novel features include graphical visualization of enrichment results and gene characteristics, and application program interface access to KEGG and STRING for the retrieval of pathway diagrams and protein-protein interaction networks. ShinyGO is an intuitive, graphical web application that can help researchers gain actionable insights from gene-sets. AVAILABILITY AND IMPLEMENTATION: http://ge-lab.org/go/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

BACKGROUND: RNA-seq is widely used for transcriptomic profiling, but the bioinformatics analysis of resultant data can be time-consuming and challenging, especially for biologists. We aim to streamline the bioinformatic analyses of gene-level data by developing a user-friendly, interactive web application for exploratory data analysis, differential expression, and pathway analysis. RESULTS: iDEP (integrated Differential Expression and Pathway analysis) seamlessly connects 63 R/Bioconductor packages, 2 web services, and comprehensive annotation and pathway databases for 220 plant and animal species. The workflow can be reproduced by downloading customized R code and related pathway files. As an example, we analyzed an RNA-Seq dataset of lung fibroblasts with Hoxa1 knockdown and revealed the possible roles of SP1 and E2F1 and their target genes, including microRNAs, in blocking G1/S transition. In another example, our analysis shows that in mouse B cells without functional p53, ionizing radiation activates the MYC pathway and its downstream genes involved in cell proliferation, ribosome biogenesis, and non-coding RNA metabolism. In wildtype B cells, radiation induces p53-mediated apoptosis and DNA repair while suppressing the target genes of MYC and E2F1, and leads to growth and cell cycle arrest. iDEP helps unveil the multifaceted functions of p53 and the possible involvement of several microRNAs such as miR-92a, miR-504, and miR-30a. In both examples, we validated known molecular pathways and generated novel, testable hypotheses. CONCLUSIONS: Combining comprehensive analytic functionalities with massive annotation databases, iDEP ( http://ge-lab.org/idep/ ) enables biologists to easily translate transcriptomic and proteomic data into actionable insights.

Using harvestable energy in Wireless Sensor Networks (WSNs) has gained considerable popularity recently. However, how to utilize the unstable power supply to achieve quality performance is still a challenge. In this paper, we propose a Weight-Optimized Source Rate Optimization (WOSRO) approach which allows the WSN system to adaptively control source coding rates by choosing the most valuable data packets to transmit. In this approach, the packet selection strategy is optimized by considering multimedia distortion reduction, energy cost, energy neutrality constraint and power saving efficiency. Simulation results show that the proposed data packet selecting strategy significantly improves data transmission quality by exploring harvesting-storage energy neutrality and multimedia data packet importance.