BRAIN TUMOUR ANALYSIS PROJECT

Oncologists often use MRI scans to identify the tumour region within a brain. Unfortunately, these scans typically reveal only a portion of the tumour. This means the obvious treatment --- irridating all-&-only the visible tumour region --- is not effective, as the "occult" tumour will continue to thrive, to the patient's detriment. Many physicians will therefore irridate a 2cm margin around the visible region; unfortunately, it is not clear that this enlarged region contains only tumour, nor that it contains all of the tumour.

​We are therefore seeking a way to predict the location of the occult tumour cells. Given the assumption that these regions that are occult today will become visible later, we are therefore attempting to learn how the tumour will grow, as a function of tumour's location and other properties (size, type). As training data, we have access to the data (MRI scans, etc) from 650 previous patients, where each patient visited between 1 and 11 times, often over years.

​This is a joint project with members of the Cross Cancer Institute.

COMPUTATIONAL PSYCHIATRY

Using computational tools to understand psychiatric disorders.

THE HUMAN METABOLOME PROJECT

Identifying and describing metabolites (small molecules)

• Bayesil, for NMR analysis​

• CFM-ID, for ESI MS analysis

• BioTransformer, to understanding reaction

MACHINE LEARNING FOR MEDICAL TASKS

Using genomic, proteomic and metabolic information to help determine which patients will respond to some specific cancer treatment

POLYOMX: PATIENT-SPECIFIC TREATMENT FOR CANCER PATIENTS

The PolyomX Project represents a systematic approach to link the knowledge gained from the human genome project to healthcare. It was established to take advantage of Alberta's unique, province-wide cancer registry. This registry, established in 1975, allows institutes such as the Cross Cancer Institute (CCI) to centralize the diagnosis, treatment and follow-up of all of the province's cancer patients. This centralized cancer registry also allows the CCI researchers access to thousands of anonymous tumor and blood samples as well as anonymized patient profiles. The result is a one-of-a-kind tumor bank that allows large-scale population studies to be performed at a genome-wide level.

These samples are then analyzed using the most recent advances in genomics, proteomics, metabolomics and bioinformatics, towards developing a broad-spectrum molecular analysis of human cancers and their correlations to certain clinical outcomes. We anticipate that this wealth of information will lead to major advances in the fight against cancer, eg, helping us to understand why some patients benefit from a given drug while others suffer adverse reactions.

To date, we have results on...

• predicting which women are likely to develop breast cancer

• which men will have long-term bleeding problems after applying radiation treatment to address prostate cancer

We plan to pursue similar studies with the other types of cancers already being tumor-banked here: (breast), lung, ovarian, gastro intestinal/colorectal, lymphoma, prostate and certain leukemia. We will also extend these analysis to include other patient information, including gene-expression data (from microarrays) and metabonomic information (eg, based on NMR-based urinalysis).

This is a joint project with members of the Cross Cancer Institute.

PROTEOME ANALYST

The Proteome Analyst is a web server designed to predict protein properties, such as general function and subcellular localization, in a high-throughput fashion.