Genedata Releases a Breakthrough for Genomic Comparison
News Jul 22, 2015
Genedata has announced the release of Genedata Selector 4.0. This latest version of the industry's leading genome knowledge management solution provides new capabilities for reference-independent genome sequence comparisons while reducing data processing and analysis time.
Genedata Selector 4.0's powerful new comparative genomics functionalities make it possible for the first time to compare and interpret genomic variants across assemblies and sequencing approaches. At the same time, the new automated processing pipeline optimizes user efficiency and lowers costs throughout the workflow, from integrating new knowledge, maintaining existing knowledge and interpreting data to generating reports.
First-In-Class Reference-Independent Genomic Comparison and Analyses Across Lineages: Genedata Selector 4.0 Addresses Current Challenges
High-quality reference genomes serve important roles in identifying and understanding genomic variants across strains and lines. As new reference assemblies become available over time, organizations are faced with a significant challenge in order to retain existing knowledge and integrate it with the new references. Information from past analyses and the related intellectual property is often lost or dispersed over time, and no longer available for use in the discovery process. For researchers, the comparison of variants across reference systems is a difficult and time-consuming task, while for bioinformaticians, the re-alignment of historic data to new reference genomes is a challenge.
Other data management systems that store variants relative to reference assemblies do not enable the performance of analyses that span different reference systems, or between genomes that are assembled without a reference genome (for example, de novo sequencing methods). Keeping all of the constantly accumulating variant knowledge current and accurate involves vast amounts of data, placing high demands on hardware and IT resources. As sequencing costs decrease and de novo sequencing approaches become more prevalent, there is a pressing need for knowledge management solutions with fewer limitations which reduce pressure on resources.
Genedata Selector 4.0 has been specially designed to meet these challenges. New genome assemblies and re-sequenced genomes can now be easily integrated with existing genomic knowledge through a new processing pipeline which automatically updates variant data from previous analyses. Users now have the ability to analyze genomic sequences and protein affects across any available reference assembly. This includes choosing a reference from within the user interface, or directly comparing variants independent of any reference genome.
Highlights of the new version of Genedata Selector:
• Efficient, flexible management of variant data
• An automated and scalable processing pipeline for easy integration of new genomes and calculation of genomic sequence differences
• Interactive exploration, comparison and fast interpretation of genomic variant information
• Querying and analysis of variant knowledge with no restrictions on the reference genome or sequencing approach used
These new features are tightly integrated with the robust knowledge management and data analysis capabilities of the platform - capabilities currently valued by customers across a wide range of industries. Within a single, integrated framework, Genedata Selector manages and analyzes genome-related data for strain and cell line optimization.
"We are very proud to provide organizations with unique functionalities integrated in a single platform to generate new insights into their data while creating efficiencies and reducing costs," said Dr. Othmar Pfannes, CEO of Genedata. "With version 4.0, we enable researchers to fully leverage the most advanced technologies used in genome-based research and we are firmly committed to continually advancing this platform to meet their emerging needs."
Is there a link between differences in IQ test performance and the activity of certain genes? Researchers have shown that modifications in the structure of a specific gene have a negative impact on individual test performance. This suggests that environmentally-induced epigenetic changes to our genetic material have a greater impact on intelligence than previously thought.
Artificial intelligence is having a positive impact on drug development and personalized medicine. With the ability to efficiently analyze small datasets that focus on the specific disease of interest, small dataset-based AI platforms can rationally design optimal drug combinations that are effective and based on real experimental data and not mechanistic assumptions or predictive modeling.READ MORE