Agilent Technologies has introduced GeneSpring GX 11.5, an expansion of its popular bioinformatics software into visualising and analysing multiple types of biological data. GeneSpring GX 11.5 now interprets exon microarray, proteomics and metabolomics experiments together for the first time, using a familiar interface. It also adds new capabilities for alternative splicing, metabolomics and proteomics analysis, as well as enhancements to existing analytical and visualisation tools.
These new capabilities join existing GeneSpring GX applications for gene expression analysis, genomic copy number analysis, genome-wide association analysis and transcriptomics data analysis. Developed in conjunction with Strand Scientific Intelligence, GeneSpring GX 11.5 is powered by Strand’s Avadis platform which has been designed to enable scientists to simplify and solve complex life science challenges.
For genomics, the splicing analysis in GeneSpring GX 11.5 has been greatly extended and enhanced to support the new Agilent exon array platform. The company’s SurePrint G3 Exon Microarrays enable researchers to identify both gene-level and exon-level expression changes in a single experiment, in order to capture subtle but important biological changes. The GeneSpring GX 11.5 bioinformatics system enhances productivity by enabling investigators to analyse the data at the gene and exon splicing levels simultaneously to understand complex gene expression behaviour in a biological context.
The new metabolomics and proteomics analysis capabilities result from integration of Agilent Mass Profiler Professional into GeneSpring GX 11.5, bringing the full capabilities of Agilent’s mass spectrometry-based analysis into the GeneSpring platform. Researchers can now have multiple experiment types representing transcriptomics, genomics, metabolomics and proteomics open in a single window. This allows users to move back and forth between experiments as needed, without having to load each one separately.
Additionally, users can compare heterogeneous data with ease and perform in-depth biological contextualisation. Automatic translation of probes across different microarray platforms and organisms allows researchers to compare results through simple drag-and-drop functionality. This seamless translation also enables them to quickly identify entity lists that share a statistically significant overlap in content.
