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Copy Number Analysis Module, GenBank 162.0, Biopython 1.44, ProteinCenter, MIRA 2.9.15

Golden Helix has released the Copy Number Analysis Module, its first software tool for whole-genome copy number variation association studies.
The software is designed to rapidly scan through high-resolution microarray intensity data to identify copy number deletions and amplifications, the company said.
CNAM has been validated on several simulated data sets with known properties as well as whole-genome Illumina and Affymetrix HapMap data with known regions of copy number variation, according to the company.

GenBank 162.0 is available via FTP from the National Center for Biotechnology here.
The new release contains 81,563,399,765 base pairs of non-whole-genome-shotgun sequence and 10,200,3045,298 base pairs of WGS sequence. Uncompressed, the 162.0 release flat files require about 305 GB for sequence files only. The ASN.1 data require approximately 281 GB.

Biopython 1.44 is now available for download here.
This release includes code improvements and fixes in the Blast interface and parsers, sequence input/output, the SwissProt parser, the clustering routines, as well as a brand new module for population genetics, according to the Biopython development team.

Proxeon has released a new version of its proteomics data-interpretation software, ProteinCenter. New features include the ability to link quantitative proteomics data to pathways and biological annotation. In addition, ProteinCenter can now handle quantitative data from Mascot and MS-Quant.
Other improvements include visualization of compared datasets through Venn diagrams, support for the Arabidopsis and Flybase sequence databases, and a new statistical module that determines the biological significance between two datasets, further increasing the reliability of data interpretation.

The MIRA 2.9.15 sequence assembler is now available here
MIRA can assemble both de novo and mapping sequences for the GS 20 and GS FLX from Roche’s 454 Life Sciences subsidiary.
Compared to MIRA 2.9.8, MIRA 2.9.15 is faster, requires less memory, and is more accurate when working with 454 data, according to the software developer.

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