BACKGROUND: Nucleosome organization is involved in many regulatory activities in various organisms. However, studies integrating nucleosome organization in mammalian genomes are very limited mainly due to the lack of comprehensive data quality control (QC) assessment and uneven data quality of public data sets. RESULTS: The NUCOME is a database focused on filtering qualified nucleosome organization referenced landscapes covering various cell types in human and mouse based on QC metrics. The filtering strategy guarantees the quality of nucleosome organization referenced landscapes and exempts users from redundant data set selection and processing. The NUCOME database provides standardized, qualified data source and informative nucleosome organization features at a whole-genome scale and on the level of individual loci. CONCLUSIONS: The NUCOME provides valuable data resources for integrative analyses focus on nucleosome organization. The NUCOME is freely available at http://compbio-zhanglab.org/NUCOME .

With the explosive growth in data volume, the I/O bottleneck has become an increasingly daunting challenge for big data analytics. Economic forces, driven by the desire to introduce flash-based Solid-State Drives (SSDs) into the high-end storage market, have resulted in hybrid storage systems in the cloud. However, a single flash-based SSD cannot satisfy the performance, reliability, and capacity requirements of enterprise or HPC storage systems in the cloud. While an array of SSDs organized in a RAID structure, such as RAID5, provides the potential for high storage capacity and bandwidth, reliability and performance problems will likely result from the parity update operations. In this article, we propose a Log Disk Mirroring scheme (LDM) to improve the performance and reliability of SSD-based disk arrays. LDM is a hybrid disk array architecture that consists of several SSDs and two hard disk drives (HDDs). In an LDM array, the two HDDs are mirrored as a write buffer that temporally absorbs the small write requests. The small and random write data are written on the mirroring buffer by using the logging technique that sequentially appends new data. The small write data are merged and destaged to the SSD-based disk array during the system idle periods. Our prototype implementation of the LDM array and the performance evaluations show that the LDM array significantly outperforms the pure SSD-based disk arrays by a factor of 20.4 on average, and outperforms HPDA by a factor of 5.0 on average. The reliability analysis shows that the MTTDL of the LDM array is 2.7 times and 1.7 times better than that of pure SSD-based disk arrays and HPDA disk arrays.