
Proteomics analysis software
Explore how instant response drives creativity and makes it easier to analyze proteomics data.
Qlucore Omics Explorer is a D.I.Y next-generation bioinformatics software for research in life science, biotech, food and plant industries, as well as academia. The powerful visualization-based data analysis tool with inbuilt powerful statistics delivers immediate results and provides instant exploration and visualization of big 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 proteomics 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.
Does it work on my data?
Answer the four quick questions below and find out if you can use Qlucore on your data.
For more details about supported data formats and data import see Data Import or Contact us with questions.
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.
Read moreAnalysis of proteomics data using Qlucore
Using proteomics to understand cardiovascular disease
Read moreInterpreting 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.
Read moreProtein 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.
Read more