CLAWSON WINDOWS GRID COLORS KEYGEN
In cells, for example, chromosomal organization is important for gene-transcription processes. Therefore, position in the DNA sequence, i.e., chromosome location, provides a convenient and essential scaffold for both the living cell and molecular biological research.
In contrast to RNA, proteins, and metabolites, DNA is organized by a limited number of large chromosomes with relatively stable DNA sequences. Genomic information is encoded in DNA and as such retained in a fairly steady configuration. Thus, SigWin-detector provides the proof-of-principle for the modular e-Science based concept of integrative bioinformatics experimentation. ConclusionĪs we show with the results from analyses in the biological use case on RIDGEs, SigWin-detector is an efficient and reusable Grid-based tool for discovering windows enriched for features of a particular type in any sequence of values. The configuration of this basic workflow can be adapted to satisfy the requirements of the specific in silico experiment. SigWin-detector was developed using the WS-VLAM workflow management system and consists of several reusable modules that are linked together in a basic workflow. We improved the original method for RIDGE detection by replacing the costly step of estimation by random sampling with a faster analytical formula for computing the distribution of the null hypothesis being tested and by developing a new algorithm for computing moving medians. For proof-of-principle, we utilize a biological use case to detect regions of increased and decreased gene expression (RIDGEs and anti-RIDGEs) in human transcriptome maps. Here we apply an e-Science approach to develop SigWin-detector, a workflow-based tool that can detect significantly enriched windows of (genomic) features in a (DNA) sequence in a fast and reproducible way. A virtual laboratory environment with workflows, workflow management systems, and Grid computation are therefore essential. The complexity of such experimentation requires these tools to be based on an e-Science approach, hence generic, modular, and reusable. To perform in silico experimentation conveniently with this genomics data, biologists need tools to process and compare datasets routinely and explore the obtained results interactively. Thus, ever-increasing amounts of data about genomic features are stored in public databases and can be readily visualized by genome browsers. Chromosome location is often used as a scaffold to organize genomic information in both the living cell and molecular biological research.
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