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The pressure to find efficient genomic compression algorithms is being felt worldwide, as proved by several prizes and competitions. In this paper, we propose a compression algorithm that relies on a pre-analysis of the data before compression, with the aim of identifying regions of low complexity. This strategy enables us to use deeper context models, supported by hash-tables, without requiring huge...
In this paper, we propose a system to compress Next Generation Sequencing (NGS) information stored in a FASTQ file. A FASTQ file contains text, DNA read and quality information for millions or billions of reads. The proposed system first parses the FASTQ file into its component fields. In a partial first pass it gathers statistics which are then used to choose a representation for each field that...
The following topics are dealt with: signal processing and statistical approaches for functional genomics; computational biology; computational genomics and epigenomics; personal sequencing; discovery of molecular signatures and biomarkers; gene and protein sequence analysis; analysis of microarray and mass spectrometry data; denoising and compression of genomic data; regulatory network modeling,...
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