Interview series - New professor - Meet Dr. Mathieu Lavallée-Adam

Publié le lundi 12 décembre 2016

New Assistant Professor in the BMI department

Dr. Lavallée-Adam started as an Assistant Professor in the Biochemistry, Microbiology and Immunology Department in September 2016. His research focus is on developing Computational Biology to answer complex biological questions and derive knowledge about cellular mechanisms and disease processes.

Dr. Mathieu Lavallée-Adam

What is your background?

My main background is in Computer Science. I have a B.Sc. with a major in Computer Science and a minor in Biology from McGill University. I also have a Ph. D. in Computer Science with a Bioinformatics option also from McGill University. My thesis was written under the supervision of Dr. Mathieu Blanchette and Dr. Benoit Coulombe. Upon completion of my Ph.D., I wanted to expand my knowledge in proteomics and mass spectrometry technologies and therefore performed a postdoctoral fellowship in the John R. Yates proteomics lab at The Scripps Research Institute in San Diego, California. Hence, even though my main training is in Computer Science, throughout my career I was continuously exposed to Biology and Biochemistry and learned how to make meaningful contributions to these fields through the use of Computer Science techniques and algorithms.

Tell us about your research?

While we know the vast majority of the genes comprised in the human genome, we are still very far from understanding the role and function of each of these genes and of the proteins they encode in the cell. Our lab aims at revealing the inner workings of the cellular mechanisms through the computational investigation of large genomics (gene) and proteomics (protein) datasets. We design algorithms and implement software packages for the analysis of these large-scale datasets and develop tools to extract relevant biological information from such datasets more efficiently. We are particularly interested in building methods to mine proteomics datasets that contain information about the protein abundance in a sample and the interactions between these proteins. To achieve this goal, we design algorithms involving machine learning, statistics, probability theory, and graph theory that characterize biological processes and infer the function of uncharacterized proteins by quantifying them and identifying their protein interactions.

What are some applications of your work?

Characterizing the abundance of a protein and the proteins it is interacting with can provide information about the role of a given gene product. This is especially important when identifying the molecular mechanisms behind a given disease process. Our computational tools identify proteins that show a different level of abundance or different interaction partners in diseases, such as breast or prostate cancer. Such proteins are likely to be linked to the disease process. They could serve as markers to diagnose a particular subtype of breast or prostate cancer and could therefore provide crucial information about the optimal therapy for the treatment of the disease. These proteins could also serve as drug targets to cure such diseases. The algorithms we design not only provide information about the proteins that should be potentially targeted by therapeutics, but they also identify which proteins a given drug binds.

What got you interested in computational biology?

It all started when I was a junior undergraduate student looking for a summer job. I was shopping for internships in the gaming industry, but I was not as excited about them as my schoolmates were. I therefore decided to contact one of my favorite teacher for an internship in his lab. He happened to be looking for summer undergraduate students to work on bioinformatics research projects during that summer. I loved spending the summer in his lab and was working on a highly stimulating research project. This project became my first publication and the professor who took me in his lab, Dr. Mathieu Blanchette, became my mentor and Ph.D. advisor. This is when I knew I was going to work in computational biology in the future. Dr. Blanchette offered me an opportunity that defined my career and trained me in the best possible way. I will be forever grateful to him.

What’s the most interesting thing about you that we wouldn’t learn from your resume?

I am a fervent aficionado of the natural wonders of the world. I love to hike through national parks and to observe their vegetation, rock formations, waterfalls and rivers, as well as the animals they harbour. I also combine this passion with one of my favourite hobby: photography. I cherish the days I can spend in the wild with my camera capturing beautiful landscapes. I also greatly enjoy cycling. I believe that cycling is the best transportation mode to enjoy the nature surrounding us. The moderate speed of the bicycle lets you appreciate the little details, smells, and sounds of your surroundings, while also taking you efficiently to your different destinations.

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