Online Simulation

And More

  1. biomarker discovery
  2. cancer care engineering
  3. cceHUB
  4. colorectal cancer
  5. global proteomics
  6. health services research
  7. lipidomics
  8. mass spectrometry
  9. metabolomics
  10. OMIC analysis
  11. peptide synthesis
  12. population-based models
  13. proteome discovery pipeline
  14. proteomics
  15. sample acquisition
  16. screening
  17. statistical models
  18. visual analytics

Other

Support

Trouble Report

For immediate assistance browse through our support center. You can find answers to many questions in just a few minutes.

If still experiencing problems, send us a report.

required
Why the math question?

Resources: Tools

Select a "tag" (or keyword) from the list below to browse through available resources in that category.

Tag

Resources

Info

  • Select a resource to see details.

View more ›

Top Rated

The following are top-rated resources of this type.

  1. Colorectal Cancer Incidence Prediction Model

    0.0 out of 5 stars 

    16 Jun. 2008 | Tools | Contributor(s): Eric Sherer, Mohd Rahmad

    Stochastic simulation of polyp and colorectal cancer (CRC) incidence with patient age.

  2. GCxGC-MS Data Classification and Alignment

    0.0 out of 5 stars 

    02 Dec. 2008 | Tools | Contributor(s): Dabao Zhang, Min Zhang, Jason Catlin

    Align and classify GCxGC-MS data

  3. Monte Carlo Simulation for four CRC Incidence Models

    9.9 out of 5 stars 

    12 Dec. 2008 | Tools | Contributor(s): Eric Sherer

    A Monte Carlo Simulator determines the risk of colorectal cancer (CRC) development in a population by calculating multiple, individual patient trajectories.

  4. Workspace

    0.0 out of 5 stars 

    27 Apr. 2009 | Tools | Contributor(s): Nicholas Kisseberth

    Workspace

  5. Spectrum Deconvolution of LC-MS Data

    9.9 out of 5 stars 

    03 Dec. 2008 | Tools | Contributor(s): Ann Christine Catlin, George Howlett

    Spectral deconvolution differentiates analyte signals from contaminants or instrumental noise, and reduces data dimensionality to benefit downstream statistical analysis.

  6. Peak Alignment of LC-MS Data

    0.0 out of 5 stars 

    24 Jun. 2009 | Tools | Contributor(s): Ann Christine Catlin, George Howlett

    Peak alignment addresses retention time shift by recongnizing and aligning significant peaks; it then uses discrete deconvolutio to align overlapped peaks.

  7. OMIC Explorer

    0.0 out of 5 stars 

    16 Mar. 2009 | Tools | Contributor(s): Philip Livengood

    Visual exploration of GCxGC MS Data

  8. Normalization of Aligned LC-MS Data

    0.0 out of 5 stars 

    18 Jun. 2009 | Tools | Contributor(s): Ann Christine Catlin, George Howlett

    Normalization attempts to quantitatively filter overall peak intensity variations due to experiment errors such as systematic variable injection volumes loaded onto LC-MS.

  9. Significance Testing of Normalized LC-MS Data

    0.0 out of 5 stars 

    23 Jun. 2009 | Tools | Contributor(s): Ann Christine Catlin

    Several statistical significance tests are employed to identify peptide or metabolite peaks that either make significant contributions to the molecular profile of a sample or distinguish a group of samples from others.

  10. Pattern Recognition for Normalized LC-MS Data

    0.0 out of 5 stars 

    01 Jul. 2009 | Tools | Contributor(s): Ann Christine Catlin, George Howlett

    This tool provides principal component analysis (PCA), linear discriminate analysis (LDA), and canonical discriminate analysis (CDA) for data clustering on aligned, normalized LC-MS datasets.