Tutorial at ISMB 2018

Schedule and materials

Introduction (Download . (PDF, 7.9 MB))

Overview of the topics presented in the tutorial

Module I: Significant pattern mining (SPM) for biomarker discovery (Download . (PDF, 5 MB))

• The need to consider feature interactions in biomarker discovery
  
• Goal of significant itemset mining. Challenges:
  • Statistical
  • Computational
• Concept of minimum attainable P-value
• The LAMP algorithm
• Contributions to the field
  • Exploiting dependencies between patterns
  • Correction for categorical covariates
  • Interval search: Genome-wide association studies at a region level
• Outlook and conclusions

Hands-on session: Applying significant pattern mining on genomic data (Download . (ZIP, 7.3 MB))

• Step-by-step tutorial on how to run the package CASMAP

Module II: Methods to compare structured biomedical data (Download . (PDF, 11.3 MB))

• The need for data transformation in machine learning
• Kernel methods and the kernel trick
• Kernelizing the nearest neighbor algorithm
• Kernels on structured data
  • String kernels
    
  • Graph kernels
    • Random walk kernel
    • Shortest path kernel
    • Graphlet kernel
    • Weisfeiler-Lehman kernel

Hands-on session: Applying graph kernels (Download . (ZIP, 13 MB))

• Step-by-step tutorial on how to use the package graphkernels
  

Module III: Deep learning and applications to biomedical data (text mining) (Download . (PDF, 10.3 MB))

• Electronic health records (EHRs). Challenges in processing unstructured text.
  
• Traditional approaches to text mining
• Obtaining word embeddings
  • Skip-gram model
• Application: Mortality prediction using unstructured text in EHRs
  • Deep newtworks combining word embeddings
    

Installation of packages (for hands-on sessions)

Virtual machine with pre-installed packages