TOM – 03.02.2016

Group Factor Analysis

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

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:

TOM Schedule

This is a tentative schedule for spring session 2016

Date Presenter Title of presentation
03.02 Suleiman Ali Khan Group Factor Analysis
17.02 Riku Katainen Analysis and visualization tool for next generation sequencing data

Arvydas Dapkunas

Ville Rantanen

Analyzing kidney development


16.03 Simon Anders DESeq
30.03 Liye He

Phylogenetic reconstruction of cancer evolution using LICHeE

12.04 Svetlana Ovchinnikova Metric learning approaches
 27.04 Mikhail Shubin Data visualisation
11.05 Christian Benner  FINEMAP: Efficient variable selection using summary data from GWAS
25.05 TBD