My main research focus is to develop machine learning methods that can help to decipher human disease heterogeneity. This involves combining data from multiple heterogeneous sources while addressing missing data and noise, simultaneous subtyping and feature selection in very sparse settings and more. Our contributions to machine learning include novel graph-based unsupervised feature selection methods and graphical models for subtyping in GWAS. We collaborate with clinicians to ensure that our work is relevant in the clinic.

Research

Peter Gilgan Learning Center

686 Bay St, Rm 12.9708

Toronto, ON, M5G OA4

Phone: 416.813.7654 x301564

E-mail: anna {.} goldenberg {at} utoronto {.} ca

Contact

News
Nov 18: Invited talk at Duke
Nov 11: Invited talk at Brown
Oct 30: Talk at Techna Symposium
Oct 29: CIFAR talk on data integration
Oct 15: Aziz’s arXiv paper cited in Nature Methods’ News and Views as an important methodological direction to pursue for combining rare variants

2014 at a glance: Nature Methods paper published (March) and recognized as one of the 3 most influential papers at a Networks meeting at ISMB (July); 3 years at SickKids; talks at MIT LL, Harvard, Broad, Dana Farber, etc; thesis opponent in Finland; Outliers (our lab’s team) winning community phase of the RA DREAM challenge. Thanks to my fantastic lab, I’m having a blast!

Old News
Jan 6, 2015: First lecture in CSC2341 Machine learning in CompBio course
Dec 13: Another fantastic MLCB workshop at NIPS. The quality has been really great - strong methods and interesting applications
Nov 19: Opponent at Tommi Suvitaival’s thesis defence in Aalto, Finland - very special experience. 
Nov 3-5: Fantastic feedback from talks at Dana Farber and Broad partial_slides_broad.pdf
Oct: Our team’s (Outliers) models came out on top of the RA DREAM challenge community phase. Special thanks to Daniel Hidru!
Mar 4: SNF R package is now on CRAN! Special thanks to Cheng and Bo.
Feb 23: Matlab code posted for SNF
Jan 31: Our project on regulation of pubertal timing was funded by CIHR!
Jan 26: Similarity Network Fusion is online at Nature Methods ! (code, data, more) 
Jan 24: Feyyaz has graduated with Masters -      congratulations Feyyaz!
Dec: Our SNF paper has been accepted to Nature Methods! 
Sep: Bo Wang has left us for a PhD at Stanford. Good luck, Bo! We will miss you
http://www.cs.toronto.edu/~goldenberg/CSC2431Home_files/slides_for_sheila_gaynor.pdfhttp://compbio.cs.toronto.edu/SNF/http://www.nature.com/nmeth/journal/vaop/ncurrent/full/nmeth.2810.htmlhttp://compbio.cs.toronto.edu/SNF/shapeimage_3_link_0shapeimage_3_link_1shapeimage_3_link_2shapeimage_3_link_3shapeimage_3_link_4