Bioinformatics System Expanded into Integrated Biology Suite

Agilent Technologies, Inc 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. These new capabilities join existing GeneSpring GX applications for gene expression analysis, genomic copy number analysis, genome-wide association analysis and transcriptomics data analysis. GeneSpring GX 11.5 adds new capabilities for alternative splicing, metabolomics, and proteomics analysis as well as enhancements to existing analytical and visualisation tools. Agilent GeneSpring GX 11.5 was developed in conjunction with Strand Scientific Intelligence, Inc.

For genomics, the splicing analysis in GeneSpring GX 11.5 has been greatly extended and enhanced to support the new Agilent exon array platform. Agilent SurePrint G3 Exon Microarrays enable researchers to identify both gene-level and exon-level expression changes in a single experiment, to capture subtle but important biological changes. Agilent’s GeneSpring GX 11.5 bioinformatics system enhances productivity by enabling investigators to analyse the data at the gene level and at the exon splicing level simultaneously to understand complex gene expression behavior 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 the experiments as needed without having to load each experiment separately. A major differentiator of GeneSpring is the ease with which users can compare heterogeneous data and the depth with which they can perform 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 allows researchers to quickly identify entity lists that share a statistically significant overlap in content.