SpliceDisease database: linking RNA splicing and disease

RNA splicing is an important aspect of gene regulation in many organisms. Splicing of RNA is regulated by complicated mechanisms involving numerous RNA-binding proteins and the intricate network of interactions among them. Mutations in cis-acting splicing elements or its regulatory proteins have been shown to be involved in human diseases. Defects in pre-mRNA splicing process have emerged as a common disease-causing mechanism. Therefore, a database integrating RNA splicing and disease associations would be helpful for understanding not only the RNA splicing but also its contribution to disease. In SpliceDisease database, we manually curated 2337 splicing mutation disease entries involving 303 genes and 370 diseases, which have been supported experimentally in 898 publications. The SpliceDisease database provides information including the change of the nucleotide in the sequence, the location of the mutation on the gene, the reference Pubmed ID and detailed description for the relationship among gene mutations, splicing defects and diseases. We standardized the names of the diseases and genes and provided links for these genes to NCBI and UCSC genome browser for further annotation and genomic sequences. For the location of the mutation, we give direct links of the entry to the respective position/region in the genome browser. The users can freely browse, search and download the data in SpliceDisease at http://cmbi.bjmu.edu.cn/sdisease

Transitions in effective scaling behavior of accelerometric time series across sleep and wake

We study the effective scaling behavior of high-resolution accelerometric time series recorded at the wrists and hips of 100 subjects during sleep and wake. Using spectral analysis and detrended fluctuation analysis we find long-term correlated fluctuations with a spectral exponent $\beta \approx 1.0$ ($1/f$ noise). On short time scales, β is larger during wake ($\approx 1.4$ ) and smaller during sleep ($\approx 0.6$ ). In addition, characteristic peaks at 0.2–0.3 Hz (due to respiration) and 4–10 Hz (probably due to physiological tremor) are observed in periods of weak activity. Because of these peaks, spectral analysis is superior in characterizing effective scaling during sleep, while detrending analysis performs well during wake. Our findings can be exploited to detect sleep-wake transitions

ICT for Development: Illusions, Promises, Challenges, and Realizations

In this chapter we will critically examining some of the illusions, promises, challenges, and realizations of the Information Society. Handed down from the past are specific myths that may create illusions in the present and promises for the future that in effect will hamper the realization of the Information Society in its most promising forms