The new Genedata Screener 10 breaks new ground in High Content, Label-Free, and Ion Channel data analysis. It also advances management of High Throughput and Lead Optimization data across organizations.

This webinar covers the set-up of analysis protocols, automated data processing, interactive optimization of data aggregation rules, quality control on full kinetics profiles, and rule-based creation of hit lists. An opportunity to see real-world, industry examples that will introduce you to the performance and interactivity of Genedata Screener, enabling optimized and efficient analysis of label-free experiments.

This webinar provides an overview of the latest functionalities in the new Genedata Selector. Using examples from our NGS-based industrial biotech projects, see first-hand how to visualize and compare complete genome sequences, overlay expression data onto metabolic pathways, and perform mutation analysis.

This webinar provides an overview of the latest functionalities in the new Genedata Expressionist 7.0 for Mass Spectrometry. You will get a first-hand look at new analysis and visualization capabilities, which will be demonstrated with several use cases and data sets for different experiment types.

This webinar demonstrates the capabilities of Genedata Expressionist for Genomic Profiling to efficiently process, analyze, and visualize large sequence data sets. A case study involving both RNA-seq and microarray data will show how Expressionist can analyze data across different technologies. 

Scaling up the HCS infrastructure with additional instruments is a major challenge. In this webinar recording you will see how Genedata Screener can connect to data and images from any instrument, and provide a common platform for data analysis.

The Genedata Screener 9 webinar shows you the latest enhancements to Screener including improved support for HCS and time-series experiments (e.g. label-free), new applications such as fully-automatic support for within plate panel screens, result calculation via a calibration curve on the plate, and the new Condoseo interface.

This in-depth analysis of a Corning Epic^® label-free data set with Genedata Screener Kinetics Analyzer covers the set-up of analysis protocols, automated data processing, interactive optimization of data aggregation rules, quality control on full kinetics profiles and rule-based creation of hit lists separating the different mechanisms-of-action observed in the screen.

New functionalities in Genedata Expressionist Refiner Genome module, featuring processing, visualization, and analysis of next-generation sequencing and high-density microarray data.

Overview of column and row mapping functions in Genedata Analyst, highlighting flexible tools for analysis of complex data sets.

New functionalities in Genedata Expressionst Refiner MS module, featuring new Annotation Framework and enhanced usability and performance.

Genedata Screener 8 is an HCS, HTS, and Time Series Data analysis platform for all standardized screening experiments and features a redesigned UI, new normalization APIs, and replicate analysis functionality.

Overview of principles of linear models and partial least square analysis and how to use them in Genedata Analyst.

Demonstration on handling new wave of dose-response data from parallel assays and deriving useful and reliable information in real time at High Throughput. Application of Genedata Screener Condoseo and Hit Profiler modules in analysis of data for 6,500 compounds from a combined selectivity and toxicity panel.

The Genedata Expressionist Refiner Genome module for genomic profiling handles experimental data of unlimited size from different vendors and technology platforms.

Overview of efficient quality control and hit selection in high content screens. Demonstrates how to interactively optimize hit selection (including quality control), review cellular images, identify variances, and retrace analysis steps at any stage in the HCS screening process.

Focus on advanced mass spectrometry technology and software features that enable analysis of large amounts of proteomic and metabolomic data in high throughput environments.