Scientific data mining for life sciences
Interested in applying our data mining and life science expertise to your project? Contact our experts today!
Team Leader, Scientific Data Mining
Agriculture; environment; biology/biotechnology; medical technology; analytics.
Technical service highlights
We help government and industrial collaborators in the fields of health, agriculture and the environment to analyze their high-volume, complex data. We can provide valuable insights, help you draw conclusions, and suggest future research and development direction for your project. We also conduct groundbreaking, foundational and applied research, independently or in collaboration with academia.
What we offer
Based within the NRC's Digital Technologies Research Centre, our team's expertise includes the following core competencies:
- artificial intelligence
- bioinformatics and computational biology
- cheminformatics and computational chemistry
- computational geometry
- computational science
- data science, including preprocessing, mining, and interpretation
- deep learning
- machine learning
We apply our expertise to the discovery and development of:
- biologics and their manufacturing
- crops with optimized biotic and abiotic resistance
- drugs and drug targets
- health software and applications
- personalized medicine
Applications and tools
We have developed the following publically available software and applications that researchers can access and use in their work:
- Circular Secondary Structure Uncertainty Plot
- Deep Learning for Identifying cis-Regulatory Elements and Other Applications
- Gene Order Browser
- GOAL (Gene Ontology AnaLyzer)
- Microarray Manual Curation Tool
- MicroDes (Micro Array Design Tool)
- MWFD (Metabolome of Wheat Fungal Disease Database)
- Multi-View Matrix Factorization Models (MVMF) for Integrative Data Analysis
- Non-Negative Matrix Factorization (NMF) Toolbox
- OPTricluster (Order Preserving Tricluster)
- Plant Orthology Browser (POB)
- Probabilistic Graphical Models (PGM) Toolbox
- Regularized Linear Models and Kernels (RLMK) Toolbox
- Sparse Representation (SR) Toolbox
- Spectral Clustering Toolbox
Why work with us
Our strength lies in combining our extensive expertise in data science with our knowledge and experience in life science and physical sciences domains. We understand what creates value for our partners and apply a collaborative approach in helping you reach your goals.
We participate in projects with the following federal departments, universities, non-profit research centres and companies:
- Agriculture and Agri-Food Canada
- Atlantic Cancer Research Institute
- Canadian Space Agency
- ISO/IEC JTC 1/SC 42 - Artificial intelligence
- ISO/TC 307 - Blockchain and distributed ledger technologies
- McGill University
- Mount Allison University
- United States Department of Agriculture
- University of Lyon
- Université de Moncton
- University of New Brunswick
- University of Ottawa
- Anu Surendra
- Alain Tchagang, Ph.D.
- François Fauteux, Ph.D.
- Eric Paquet, Ph.D.
- René Richard
- Yifeng Li, Ph.D.
- Youlian Pan, Ph.D.
- Ziying Liu
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