Date(s) - 2015-12-09 - 2015-12-11
09:00 CET - 13:00 CET
ATC Computer Training Lab
This intermediate-level course will demonstrate through a combination of lectures and hands-on tutorials how to perform integration of heterogeneous biological data.
Integrative analytics is currently one of the hottest fields in bio-medical data research and paradoxically adding supporting information helps to reduce data complexity, and to infer a more complete picture of condition-dependent biological responses.
Requirements for participation:
- basic R – the course will be predominantly R-based, familiarity with other programing languages will suffice
- basic Cytoscape – for this course you only need to know how the CS interface is organized, contact us for a basic tutorial, which you can work through before the course
- Experimentalists with basic computational skills (own experience, or EMBL courses: Introduction to R / Python / Linux Command line, Introduction to Network Biology)
- Computationally-focused scientists (maths, bioinformatics, biology etc) with interest in learning about network-based integrative approaches
- Introduction to concepts of Graph Theory
- Mining public resources
- Network inference from data, adjacency matrices, and combining data on graphs
- Enrichment and functional integration of -omics data
- Using Kernels on graph nodes to compute similarities, and integrate heterogenous biological data
- Mining dynamic networks: third order tensors for representation of dynamic graphs, and tensor factorization for characterizing time-evolving patterns
- computing various kernels from different data sets
- evaluating kernels on information retrieval tasks
- using kernels to make predictions
- Introduction to network community structure and clustering algorithms
- Methods to detect, evaluate, and visualize community structure in complex integrated biological networks
Tutors:Matt Rogon (EMBL Centre for Network Analysis), Jean-Karim Hériché (Ellenberg Group, CBB), and Aaron Brooks (Steinmetz Group, GB)
This is an internal course free to all EMBL scientists, as well as associated students.