CASP is a data analytics platform at Umeå University that provides support and training to
life science researchers in the analysis of experimental data, using advanced data-driven tools and strategies.
The Computational Analytics Support Platform description
Our mission is to help life science researchers understand complex chemical and biological systems. This is achieved via the application and development of advanced computer-based modelling tools. CASP’s focus is on the analysis of non-genomic related data from a wide array of technologies including, but not limited to, downstream omics (e.g., metabolomics, proteomics), spectroscopy and imaging. Our approach has multiple applications in areas including health, medicine, pharmaceuticals, agriculture and the food science industries.
What we do
At present, huge amounts of data are generated not only in genomics, but also by other modern high-throughput technologies such as ‘omics’ and sensor technologies. The ability to analyze and draw valid conclusions from complex data has become a bottleneck for many life science researchers.
CASP’s aim is to overcome this by becoming the bridge between data and life sciences. We provide researchers with modern data analytics tools within multivariate data analysis, statistics, AI/deep learning, machine learning, and design of experiments for the analysis of experimental data. Ultimately, we hope to provide the missing link that enables projects to go from data to completion.
How we can help your project
Our main mission is to support researchers deliver high-quality results, by converting complex data into meaningful biological/chemical interpretations relating to their specific scientific question.
Our uniqueness arises from our expertise – we not only understand mathematics, statistics and modelling, but we have wide domain knowledge arising from active engagement in numerous projects in the ‘omics’ area and beyond. Therefore, we are able to ‘jump in’ to your project from day one and provide support every step of the way. This can mean starting from experimental design, quality control of generated data, basic and more in-depth analysis, through to interpretation of results, experimental validation and publishing.
Support and services we provide
We offer different kinds of support for all types of data and research questions:
Packaged and customer-specific data analytics projects
Personalised training - hands-on tutorials in the use of data processing and data analysis software for specific data types
Consultations for data analysis support – long-term
Extended data analytics support for UmU experimental platforms (SMC, ViSp)
Design of Experiments (DOE) / Statistical experimental design
Data preprocessing, filtering, normalization, standardization and scaling
Multivariate data analysis
Principal Components Analysis (PCA)
Partial Least Squares regression analysis (PLS)
Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA)