Group Factor Analysis

Presented by:  Suleiman Ali Khan, Post-doc, Group Aittokallio, FIMM

http://users.ics.aalto.fi/suleiman/

A key underlying problem faced by informaticians in general and computational biologists in particular is to identify the dependencies between one or more datasets. Recent advancements in machine learning have led to creation of a series of methods that could identify statistical patterns shared between multiple datasets as well as enumerating those specific to anyone. ‘Group Factor Analysis (GFA)’ is a key tool that has recently come up to address these challenges, and in the first session of TOM I will give an overview GFA and some of its practical use cases in bioinformatics and computational biology.

For more reading:

http://bioinformatics.oxfordjournals.org/content/30/17/i497.full.pdf+html

http://research.cs.aalto.fi/pml/online-papers/khan2014ecml.pdf

http://jmlr.csail.mit.edu/proceedings/papers/v22/virtanen12/virtanen12.pdf