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Click on the demo to get a quick overview. To get access to the full demos, please fill out the form below. These demos describe new technologies and techniques for proteomics and genomics research. Watch them any time that's convenient for you, and learn how you can extend your research. The demos are in English unless noted otherwise. |
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Attend a webinar or view a demo to learn more about our Software and how they're helping researchers.
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Preview of just a few of our demos in archive.
Dec-10 Profiling the Landscape of RNA-Seq Data
In this webinar, we will present Integromics® SeqSolve™ for TIBCO® Spotfire® and its original approach to characterize RNA-seq data. We will explore the analysis portfolio provided by this simple yet advanced turn-key solution for profiling the landscape of "next-generation" transcriptomic data: reads statistics (size, number, redundancy), assignment to genomic regions (exons, introns, UTR...), coverage within exons and transcripts, read density over genomic landmarks (TSS, splice sites...), differential gene expression assessment and automatic Quality Controls. Using simple examples from the literature, we will illustrate the power of a downstream "tertiary" analysis of RNA-seq data to obtain clear scientific results.
Sep-10 Genomics Data Analysis: Design, Quality Control, Statistical Analysis and more.
In Part 1, we will present Integromics Biomarker Discovery® for TIBCO® for microarray analysis and how its guided workflows and Tools, can be applied to analyze Affymetrix, Illumina, Two-Channel and CGH data. We will address questions concerning data quality, array normalization, and explore differentially expressed genes, gain understanding about the biological processes affected between the various groups of the experiment, utilize the Gene Ontology Browser to locate genes of interest in a gene ontology hierarchy and display the Pathway Viewer to reveal which pathways are implicated.
Jul-10 RT-PCR Data Analysis: Avoiding the Pitfalls with RealTime StatMiner®
Are you trying to get more out of your qPCR data? Do you need to become more efficient and more confident in your research and analysis?
