EMBL and DNASTAR Expand License Agreement to Include
News Apr 15, 2009
DNASTAR® and its German distribution partner, GATC Biotech, Konstanz, Germany, announced the expansion of its bioinformatics licensing arrangement with the European Molecular Biology Laboratory (EMBL) Heidelberg facility to include DNASTAR’s Next Generation Sequence assembly tool SeqMan NGen™. This expands the already existing arrangement between the two organizations where EMBL had recently renewed its multi-network arrangement for use of the Lasergene® software for sequence analysis.
Under the terms of the license arrangement, EMBL’s Genomics Core Facility will have access to the SeqMan NGen and Lasergene tools for use on a range of projects using multiple sequencing platforms. While Lasergene continues to be one of the leading DNA sequence analysis software packages commercially available, its utility has been enhanced by the addition of the SeqMan NGen assembly tool to allow it to be used for both conventional and second generation sequencing types of projects.
The company has reported considerable interest in this “graduate” approach which permits existing Lasergene users to move up to sequence assembly and analysis of high throughput sequencing platform data while continuing to use familiar software.
SeqMan NGen is an assembly tool specifically designed to be used in large sequencing projects where new Next Generation Sequence platforms are being used. Its desktop computer focus and ability to work with a wide range of project assembly sizes due to its RAM-dependent design. Compatibility with a well-known analysis software suite, Lasergene, simplifies analysis and user ramp-up times.
The EMBL facility joins a growing list of public and private organizations that are adopting Next Generation Sequencing platforms from a variety of manufacturers and that are realizing the benefits of building on an analysis software suite in their facility to reduce support time.
Changing Lanes: Algorithm Helps AI Drive More Like HumansNews
For self-driving cars, algorithms for changing lanes are beset by one of two problems. Either, they rely on detailed statistical models of the driving environment, which are too complex to analyze on the fly; or they’re so simple that they can lead to impractically conservative decisions, such as never changing lanes at all. Now a new algorithm hopes to split the difference, allowing aggressive lane changes than the simple models do but relies only on immediate information about other vehicles’ directions and velocities to make decisions.
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