|
|
Below is a list of current members along with a short description of each member's research interests and links to personal web pages.
| Name
| Research Area |
Affiliation |
|
| |
| Miguel Andrade
| Health research |
Cellular and Molecular Medicine - UOttawa |
| Stephane Aris-Brosou
| Molecular evolution |
Biology - UOttawa |
| Frank Dehne
| Parallel computing and Bioinformatics |
Computer science - Carleton University |
| Guy Drouin
| Molecular evolution |
Biology - UOttawa |
| Michel Dumontier
| Bioinformatics |
Biology - Carleton University |
| Fazel Famili
| Data mining, Bioinformatics |
Information Technology and Engineering - UOttawa |
| James Green
| Machine learning and Bioinformatics |
Systems and Computer Engineering - Carleton University |
| Jeremy Kerr
| Ecology and Conservation |
Biology - UOttawa |
| John Lewis
| Computational neuroscience |
Biology - Uottawa |
| André Longtin
| Neurophysics and nonlinear dynamics |
Physics - Uottawa |
| Frithjof Lutscher
| Spatial ecology and Evolution |
Mathematics and Statistics - Uottawa |
| Anne-Gaelle Rolland-Lagan
| Systems biology and Development |
Biology - UOttawa |
| David Sankoff
| Evolution, comparative genomics |
Mathematics and Statistics - UOttawa |
| Tom Sherratt
| Evolutionary Ecology |
Biology - Carleton University |
| Robert Smith?
| Modelling of Infectious diseases |
Mathematics and Statistics - UOttawa |
| Marcel Turcotte
| Bioinformatics |
Information Technology and Engineering - UOttawa |
| Gabriel Wainer
| Modelling methodology |
Systems and Computer Engineering - Carleton University |
| Xuhua Xia
| Bioinformatics, Molecular evolution |
Biology - UOttawa |
| Miguel Andrade - Health research - University of Ottawa
Email: mandrade@ohri.ca
Web: http://www.ottawagenomecenter.ca/research/bioinformatics/mandrade/ - http://www.ottawagenomecenter.ca/research/bioinformatics
My group uses computation and information from biological databases to produce working hypothesis for experiments in the field of health research. We have a focus on analysis of high throughput genomics data and in particular of data obtained from stem cells. We collaborate with many experimental groups in the University of Ottawa, but also national and internationally.
Keywords: Data mining, DNA microarray data analysis, stem cells, text mining, protein sequence analysis, databases.
Courses taught: Participation in CSI4126 - Algorithms in bioinformatics, BPS4101 Human Genome Structure and Function, CMM 5304 - Developmental Biology, BCH 8110 Advanced Topics in Systems Biology, Stem Cell Network Microarray Analysis Course online here.
Background useful for interested students: Students interested in working in my group should be proficient in computer programming. Understanding of basic biology is helpful, but not absolutely necessary. And of course experience using bioinformatics tools and databases is very much appreciated. |
 |
| Stephane Aris-Brosou - Molecular evolution - University of Ottawa
Email: sarisbro@uottawa.ca
Web: http://aix1.uottawa.ca/~sarisbro/
- Comparison of molecular phylogenies - Estimation of molecular phylogenies and divergence dates- Codon substitution Markov models and detection of adaptive molecular evolution.
Keywords: Molecular evolution, bioinformatics.
Courses taught: BIO 3502 - evolution moleculaire [hiver 2008 seulement]- BIO 3519 - genetique des populations [a partir hiver 2009]- BIO 4134C - Mathematical methods in biology- BPS 4504 - laboratoire de bioinformatique- BIO 5106 - Bioinformatics- BIO 5506 - Bioinformatique
|
| Frank Dehne - Parallel computing & bioinformatics - Carleton University
Email: frank@dehne.net
Web: http://www.dehne.net
My research focuses on parallel computing and computationally hard problems in Bioinformatics. Current research includes parallel computational methods for protein interaction prediction and aptamer design.
Keywords: Parallel computing, computational biology.
Courses taught: Courses taught: BIO 5106 (BIOL 5506) Bioinformatics, COMP 5704F (CSI 5131) Parallel Algorithms and Applications in Bioinformatics.
|
 |
| Guy Drouin - Molecular evolution - University of Ottawa
Email: gdrouin@uottawa.ca
Web: http://www.biology.uottawa.ca/details.php?lang=eng&id=9 (in English) http://www.biologie.uottawa.ca/details.php?lang=fra&id=9 (en Français)
My research interests are in molecular evolution. I want to know what happens when more than one copy of a gene (i.e, a few, dozens or hundreds) is present in a genome. In particular, I want to know whether the different gene copies have different functions and whether they evolve independently from one another. I currently have three specific projects. First, we study how the genes coding for RNA polymerases I, II and III evolved, specially the selective forces that lead to the differentiation of these three RNA polymerases from a single prokaryotic RNA polymerase gene. Second, we study gene conversions in prokaryotic and eukaryotic genomes in order to evaluate the role that gene conversions have played in shaping these genomes. Third, we study the evolution of ribosomal RNA genes in fungi in order to characterize the factors influencing the evolution of these very abundant tandemly repeated genes.
Keywords: Bioinformatics, genomics, molecular evolution
Courses taught: BIO2533: Génétique, BIO5302: Évolution moléculaire, BIO4537: Génétique évolutive humaine
Background useful for interested students: Molecular Evolution (BIO3502 or BIO3102), Bioinformatics (BPS4104 or BPS4504) and Applied Statistics (BIO4158 or BIO4558). |
 |
| Michel Dumontier - Bioinformatics - Carleton University
Email: Michel_Dumontier@carleton.ca
Web: http://dumontierlab.com
My research program is focused around developing a computational platform for personalized medicine by advancing drug discovery approaches for different genetic backgrounds and predicting the outcome using cell simulation technologies. Towards this goal, we are researching fundamental issues related to 1) biochemical data integration using the semantic web technologies, 2) developing computational approaches for drug discovery, 3) building cellular models and tools for cell simulation and 4) implementing hardware accelerated (FPGA/DSP/Cell) solutions for parallel bioinformatics analysis.
Keywords: Bioinformatics, computational biology, semantic web, ontology, knowledge management, metabolic fate, cell simulation, hardware acceleration.
Courses taught: BIOC3008, BIOC4008, XXX4901, XXX4908.
Background useful for interested students: BIOC 3101 - General Biochemistry I, BIOC 3102 - General Biochemistry II, COMP 1002 - Introduction to Systems Programming |
 |
| Fazel Famili - Data mining, Bioinformatics - University of Ottawa
Email: Fazel.Famili@nrc-cnrc.gc.ca
Web: http://iit-iti.nrc-cnrc.gc.ca/personnel/famili_fazel_e.html
Dr. A. Fazel Famili is a Senior Research Scientist, Project Leader and a leading data mining expert working at the Institute for Information Technology (IIT) of the National Research Council of Canada, where he has been for over 22 years. Prior to joining NRC, he worked in industry for 3 years. Dr. Famili has been actively involved in the field of Artificial Intelligence, Data Mining and BioInformatics and successful application of these technologies. He has a strong data mining and bioinformatics team within IIT that is currently engaged in unique research and development in data mining for genomics, proteomics and health care. His research has been on data mining, machine learning and bioinformatics and their applications to real world problems in various data rich environments, such as semiconductor manufacturing, aerospace and life sciences. Dr. Famili has edited two books, has published over 40 articles in the area of data mining and AI and has a US data mining patent. He has organized
many workshops and has been involved in a number of data mining and AI conferences and has extensive collaboration with NRC Institutes and a number of other research institutes in Canada and Europe. He is also on the editorial board of four scientific journals and an adjunct professor at SITE (School of Information Technology and Engineering), and The Institute of System Biology, at the University of Ottawa.
Keywords: Knowledge Discovery, Bioinformatics, Machine Learning.
|
 |
| James Green - Bioinformatics, Machine learning and Pattern classification - Carleton University
Email: jrgreen@sce.carleton.ca
Web: http://www.sce.carleton.ca/faculty/green
My research focuses on the application of machine learning, nonlinear system identification, and pattern classification to solve problems in biology and medicine. Areas of interest include predicting protein structure, function, interaction, and post-translational modification; reverse engineering and simulating genetic regulatory networks; identifying sites that control gene expression; and the analysis of mass spectrometry data for protein identification and characterization.
Keywords: Bioinformatics, computational proteomics, machine intelligence, pattern classification
Courses taught: SYSC5108 – Pattern Classification and Experiment Design.
Background useful for interested students: Any courses in bioinformatics and machine intelligence/pattern classification. Either a strong background in molecular biology or a strong background in computer science/engineering is required, so long as there is an interest by the student to learn their intersection. |
 |
| Jeremy Kerr - Ecology and Conservation - University of Ottawa
Email: jkerr@uottawa.ca
Web: http://www.science.uottawa.ca/~jkerr
Professor Kerr's research focuses on three key areas: global change impacts on biodiversity, conservation biology, and macroecology. His research group at the Canadian Facility for Ecoinformatics Research (CFER) uses quantitative models, remote sensing, and geospatial ecological tools to answer key questions in these areas. The broad goals of this research program bridge the gap between pure (i.e. macroecology) and applied research to help reduce extinction rates in the face of unprecedented environmental change.
Keywords: Macroecology, climate change, land use change, endangered species, biodiversity, conservation biology
Courses taught: BIO 2129 - Introduction to Ecology, BIO 4150 - Spatial Ecology, BIO 8102 - Advanced topics in spatial ecology, BIO 3103 - Tropical island and reef ecology
Background useful for interested students: Spatial ecology and practical courses on geographic information systems and/or remote sensing. |
 |
| John Lewis - Computational neuroscience - University of Ottawa
Email: john.lewis@uottawa.ca
Web: http://aix1.uottawa.ca/~jlewis
The dynamics underlying brain activity arise from processes occurring at many levels, from network feedback interactions, to the sub-cellular processes involved in synaptic plasticity. Our goal is to understand how the brain uses these processes to encode and interpret sensory information, whether that is to produce a specific behaviour or to store the information as a memory.
The weakly electric fish is particularly well-suited for these studies. These fish have evolved an exquisite electric sense that enables them to capture prey and communicate in dark and murky waters. While the brain structures involved in the electric sense are relatively simple, they exhibit many similarities with our own sensory systems. Our approach is multidisciplinary, using techniques ranging from cellular electrophysiology to computational modeling and behavioural analyses.
Keywords: computational neuroscience, neural dynamics, neuroethology, synaptic plasticity.
Courses taught: Bio3305 Cellular Physiology, Bio3137 Experiments in Animal Physiology, Bio4350 Principles of Neurobiology, Bio4351 Neural Basis of Animal Behaviour, NSC8104 Computational Neuroscience Summer School (graduate course)
|  |
| Frithjof Lutscher - Spatial ecology and Evolution - University of Ottawa
Email: flutsche@uottawa.ca
Web: http://www.mathstat.uottawa.ca/~fluts037/
I use dynamical-systems type mathematical models to investigate how individual movement processes and dispersal strategies affect population-level outcomes such as persistence and extinction, range boundaries, effects of competition, stability.
Keywords: Dispersal, reaction-diffusion equation, integrodifference equation, biological invasion, reserve design.
Courses taught: Calculus, linear algebra, differential equations, dynamical systems, mathematical biology (I hope, soon), BIO 4134/MATH4996.
Background useful for interested students: Strong analysis and dynamical systems, interest in ecology and evolution. |
 |
| Anne-Gaelle Rolland-Lagan - Developmental biology and Systems biology - University of Ottawa
Email: arolland@uottawa.ca
Web: http://www.science.uottawa.ca/~arolland/
Ever wondered how a zebra gets its stripes, or how, from a few cells, a plant or animal grows into its particular shape? As an organism grows, different sets of genes are expressed in different parts, which affect development. But how? What controls shape as an organism develops? How does the changing shape and size of an organism as it grows affect spatial and temporal patterns of gene expression?
This is an exciting time for developmental biology, as recent advances in molecular biology, 2D and 3D imaging, and computer technology now make it possible to investigate these questions.
In our lab, we use a combination of experimental work (e.g. fluorescence microscopy), computational tools (e.g. image processing) and simulation modeling to investigate mechanisms of morphogenesis.
Keywords: Pattern formation, growth, systems biology, image processing, image analysis, simulation modeling, plant development.
Courses taught: BIO4140/BIO4540 Plant developmental biology,BIO3140 Plant physiology and Biochemistry, BIO4134.
Background useful for interested students:
I am looking for enthusiastic, highly motivated students to work in the area of developmental biology. Specific areas include: 1) the study of pattern formation mechanisms in plants, and 2) plant cell morphogenesis. I also welcome proposals dealing with pattern formation and growth in animal systems. To work in the lab, you need either a computer science background (ideally computer graphics) with an interest in biology, or a general biology background, with basic knowledge in computer programming (e.g. CSI1308) and a keen interest in morphogenesis. Experience in Matlab programming is an asset. |
 |
| David Sankoff - Evolution, comparative genomics - University of Ottawa
Email: sankoff@uottawa.ca
Web: http://albuquerque.bioinformatics.uottawa.ca/
Mathematical and probability models of chromosomal rearrangements in evolution, with applications to comparative genomics.
Courses taught: every year one or two courses called "topics in..." either applied math, statistics, probability, or algorithms. This is a combined graduate/upper level undergraduate seminar course, which changes number according to the name, but which is basically on mathematical and probability models of chromosomal rearrangements in evolution, with applications to comparative genomics.
|
 |
| Tom Sherratt - Evolutionary Ecology - Carleton University
Email: sherratt@ccs.carleton.ca
Web: www.carleton.ca/~sherratt
My research interests comprise two main themes: (a) how individual behaviour helps to shape the spatio-temporal dynamics of populations and (b) the evolution of behaviour. My interests in spatio-temporal dynamics are both pure and applied in nature. In particular, I have investigated the causes of synchrony and higher-order spatio-temporal phenomena such as travelling waves in natural populations, and have developed and tested models of the way in which populations recover following the application of toxicants. My interest in the evolution of behaviour has centred on elucidating the factors that have influenced the emergence of some unusual phenomena such as cannibalism, superparasitism, mimicry and co-operation between non-relatives.
Much of my research is theoretical, and employs tools such as genetic algorithms, dynamic programming and cellular automata. However I also maintain an experimental research program to complement this research, which is predominantly entomological in nature. For example, I have investigated the population genetics of aphids, the evolutionary significance of cannibalism in neotropical mosquitoes, the dispersal behaviour of dragonflies and the use of tropical butterfly communities as indicators of ecological change. Some of this work has been based in Trinidad, and I have also conducted more recent work in Sabah, North Borneo and Viti Levu, Fiji.
Keywords: evolution, behaviour, population dynamics, theoretical ecology.
Courses taught: BIOL 3612 Computational methods in ecology and evolution, BIOL 3604 Analysis of ecological relationships, BIOL 5409 Mathematical modelling for biologists, BIOL 5407 Quantitative ecology.
Background useful for interested students: I am happy to consider suitably-qualified students, leading to MSc or PhD, for field and theoretical work in the areas of: (a) anti-predator defence (in particular mimicry and warning signals), (b) genetic polymorphisms and (c) the spatio-temporal dynamics of populations. I would also be happy to consider thesis proposals outside these general areas. The main requirements are (i) good grades (essential for securing funds) (ii) a genuine enthusiasm for ecology and evolutionary biology. Students with quantitative skills (e.g. mathematical or computer modelling) are particularly encouraged to apply.
I’m also happy to consider undergraduate dissertation projects. Main requirement is a genuine enthusiasm for ecology and evolution. It also helps that you have a broad notion of what you would like to work on. |
 |
| Robert Smith? - Modelling of Infectious diseases - University of Ottawa
Email: rsmith43@uottawa.ca
Web: http://www.mathstat.uottawa.ca/~rsmith
My research involves the application of mathematical models to study infectious diseases. I mostly study HIV, but am also interested in malaria, West Nile virus, Human Papilloma virus and Chagas' disease. Of particular interest is the application of control methods, such as drugs, vaccines, microbicides and other interventions. The mathematical theory I use to study these diseases involves impulsive differential equations; these are differential equations with discontinuous jumps that depend on either the time of impulse, the state of the system immediately before an impulse, or a combination of both.
Keywords: Infectious diseases, HIV, malaria, vaccines, microbicides, adherence, mathematical modelling, impulsive differential equations.
Courses taught: MAT1332 (currently), MAT1330, MAT3130, BIO4134 (forthcoming).
Background useful for interested students: MAT1330, MAT1332. |
 |
| Marcel Turcotte - Bioinformatics - University of Ottawa
Email: turcotte@site.uottawa.ca
Web: http://www.bio.site.uottawa.ca/~turcotte - http://www.bio.site.uottawa.ca
A bioinformatics approach to the identification of RNA structural motifs. We develop new tools to identify higher-order functional RNA motifs. The patterns that are sought consist of primary, secondary and/or tertiary structures. Accordingly, new algorithms will be developed to search for common grammatical structures, secondary expressions, in a set of related genomic sequences or RNA transcripts. Goal: automatically discover transciptional regulatory motifs.
Keywords: Nucleic acids, structure, pattern discovery, algorithms design
Courses taught: CSI 5126. Algorithms in bioinformatics.
|
 |
| Gabriel Wainer - Modelling methodology - Carleton University
Email: gwainer@sce.carleton.ca
Web: http://www.sce.carleton.ca/faculty/wainer/
Our laboratory is investigating means of automatic generation of executable models derived from systems specifications. The research is based on the Discrete EVent System specification (DEVS) formalism, and will augment previous work with new theory, methodology, and supporting development tools. We are also interested in integrating the simulation results obtained with powerful 3D visualisation facilities. We use advanced modeling and simulation techniques for modeling complex biological applications, including extensions to cellular automata and discrete event simulation models. We are exploring advanced systems biology languages and their interface with simulation models, and model database technologies with application to biological exploration.
Keywords: DEVS formalism, Real-Time modelling, Cellular models, Modelling and simulation methodologies and tools, Parallel/distributed/Web-based simulation
Courses taught: SYSC5104
Background useful for interested students: SYSC5104. |
 |
| Xuhua Xia - Bioinformatics, Molecular evolution - University of Ottawa
Email: xxia@uottawa.ca
Web: http://dambe.bio.uottawa.ca
I study bioinformatics, molecular evolution and phylogenetics. Specific projects include evolution and adaptation of pathogens (e.g., Helicobacter pylori) in their host and emergent diseases, characterization of translation initiation signals and elogation efficiency in prokaryotic and eukaryotic species, development of bioinformatic tools for descriptive, comparative and functional genomics.
Keywords: bioinformatics, genomics, molecular evolution, phylogenetics, computation, stochastic processes
Courses taught: BIO4138: Bioinformatics and the cell, BPS4104: Bioinformatics Laboratory, BIO8100: Recent advances in bioinformatics and molecular evolution.
|
 |
|
|
|
