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LAB EXECUTION AND ANALYSIS

Complete experiment design, execution, analysis and reporting software for high-throughput parallel laboratory automation.

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LEA Decision Support Overview

Accelrys LEA decision support software (PolyView and Spectra Studio) enables scientists to query, visualize and analyze experimental data acquired through LEA software.

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PolyView

PolyView is a sample-based querying and reporting tool that is capable of correlating multiple experimental figures. Use PolyView to access and analyze data captured from multi-step screening, synthetic and analytical processes collected through the lifetime of a test sample. Automatically cluster results based on spectra similarity or XY data set profile to rapidly identify novel or existing samples

With PolyView you can:

  • Find samples based on any logical combination of experiment values saved to the database. Search the entire database or restrict by list.
  • Add, subtract or combine lists to create new ones
  •  Create reports dynamically. Choose from a wide selection of visualizations including spreadsheets, grids, 2D and 3D plots, and overlays with supporting experimental data
  • Tile your visualizations for side-by-side comparison. Find data trends by selecting elements in one visualization to highlighted corresponding elements in others
  • Compare spectra or chromatograms automatically in an overlay view with the experimental details of selected samples, including design information from Accelrys Library Studio

Spectra Studio

Scientists use Spectra Studio to compare and contrast images and spectra from high-throughput experimentation to make informed decisions about experimental results. Identify novel versus known spectral data by viewing, smoothing, comparing and clustering similar spectra (Raman, FTIR, XRD) acquired through Accelrys LEA software.

With Spectra Studio you can:

  • Load spectra spanning multiple experiments and multiple libraries from the database and sort into clusters
  • Sort using algorithms based on comparing raw data, peak centers, peak overlaps and first derivatives
  • Use control sample spectra to support clustering and assigning of tested samples
  • Enable multiple spectra preprocessing options; smoothing data, restricting the sort to specific regions of interest and establishing criteria for identifying questionable or invalid spectra
  • Analyze spectra in multiple views including: clustered bins, library-based layout or as an overlay of the selected spectra

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