Proteomics

Explore how instant response drives creativity and makes it easier to analyze proteomics data.

ANALYZE PROTEOMICS DATA

Proteomics is the large-scale study of proteins, particularly their expression and physical properties. Commonly quantitative methods used in proteomics are 2D gel, LC-MS and LC-MS/MS.

Qlucore Omics Explorer lets the researcher freely examine and analyze data from protemics experiments. 

Key functionality:

  • Investigate any structure in data using variance filtering combined with PCA.
  • Perform statistical filtering using ANOVA to enhance results.
  • Generate a list of proteins that classifies data based on a selection of statistical tests: F-test, t-tests or regression.
  • Use hierarchical clustering or PCA to indentify subgroups.
  • Work with Variable PCA plots to find correlation and networks among selected proteins.

Easy data import

Qlucore Omics Explorer supports many data file formats. Import can be done in several ways, with or without normalization. 

Learn more

Case Studies

Analyzing proteomics and transcriptomics data

Study of hundreds of entries about pollutants and nutrients in different fish species, showing how levels are changing over time.

National Institute of Nutrition and Seafood Research (NIFES), Norway

Read more

Analysis of proteomics data using Qlucore

Using proteomics to understand cardiovascular disease

The Center for Interdisciplinary Cardiovascular Sciences, Boston, US

Read more

Interpreting Leukemia proteomics with Qlucore

In this case study Qlucore Omics Explorer is used to generate new ideas and hypotheses through exploration and analysis of proteomics data.

UT MD Anderson Cancer Center in Houston, Texas, US

Read more

Protein data analysis in Hepatitis studies

Understanding viral signatures in Hepatitis C. Qlucore Omics Explorer is used to identify differences in chemokines between the virally infected groups.

Institute Pasteur, France

Read more