Marcel Turcotte

800 King Edward · Ottawa ON Canada · K1N 6N5 · (613) 562-5800, 7441 · marcel.turcotte@uottawa.ca

Marcel Turcotte is a Computer Science Professor at the University of Ottawa’s School of Electrical Engineering and Computer Science. His research interests include bioinformatics, nucleic acids, applications of machine learning, and algorithm design.


Education

Université de Montréal

Philosophiae doctor (Ph.D.) in Computer Science
Génération et traitement de contraintes relationnelles pour la modélisation des acides nucléiques

Supervisors: Guy Lapalme (Computer Science) and Robert Cedergren (Biochemistry)

December 7, 1995

Université de Montréal

Master of science (M.Sc.) in Computer Science
Fast-Track from the Master’s to the Ph.D.

Supervisors: Guy Lapalme (Computer Science) and Robert Cedergren (Biochemistry)

November 4, 1993

Université de Montréal

Bachelor of science (B.Sc.) in Computer Science
October 18, 1989

Experience

Director, Program Evaluation

Office of the Vice-Provost, Academic Affairs

Responsible for cyclical reviews of undergraduate and graduate programs and manages the processes; chairs both program evaluation committees; sits on both councils (undergraduate and graduate studies).

July 2020 - June 2023

Vice-Dean, Undergraduate Studies

Faculty of Engineering

An Officer of the Faculty and is a regular member of the Faculty Executive Committee. The Vice-Dean (Undergraduate Studies) is responsible for the development and administration of the undergraduate academic programs of the Faculty of Engineering, including recruitment, admissions, and retention. The Vice-Dean (Undergraduate Studies) provides support for professional accreditation.

January 2012 - June 2018

Computer Science Professor

School of Electrical Engineering and Computer Science (EECS)

Students often say that I am knowledgeable and have a sense of humor. I take time to answer questions inside and outside of class. My notes, homework, laboratories and solutions are very organised. I am also known to give candy while lecturing stacks.

July 2000 - Present

Postdoctal fellow

Imperial Cancer Research Fund (ICRF), U.K.

Applied Inductive Logic Programming (ILP) to learn signatures of protein folds. Under the supervision of Michael J.E. Sternberg, in collaboration with Stephen H. Muggleton.

June 1997 - June 2000

Postdoctal fellow

University of Florida, U.S.A.

Worked on the development of protein secondary structure prediction methods using evolutionary information. Under the supervision of Stephen A. Benner.

September 1995 - May 1997

Research

Academic profile

Publications

Papers submitted to refereed journals

  1. Kevin Sutanto and Marcel Turcotte. Assessing global-local secondary structure fingerprints to classify RNA sequences with deep learning. IEEE/ACM Transactions on Computational Biology and Bioinformatics Special Issue, Submitted on 2021-02-28; Major Revision Requested on 2021-05-12.

Papers in refereed journals

  1. Aseel Awdeh, Marcel Turcotte, and Theodore J. Perkins. WACS: improving ChIP-seq peak calling by optimally weighting controls. BMC Bioinformatics, 22(1):69, 2021.
  2. Alexander Gawronski and Marcel Turcotte. RiboFSM: Frequent subgraph mining for the discovery of RNA structures and interactions. BMC Bioinformatics, 15 Suppl 13:S2, November 2014.
  3. Ghada Badr, Isra Al-Turaiki, Marcel Turcotte, and Hassan Mathkour. Incmd: Incremental trie-based structural motif discovery algorithm. Journal of Bioinformatics and Computational Biology, 12(05):1450027, October 2014. PMID: 25362841.
  4. Georgette Kiethega, Yifei Yan, Marcel Turcotte, and Gertraud Burger. RNA-level unscrambling of fragmented genes in Diplonema mitochondria. RNA biology, 10(2):301–313, January 2013.
  5. Georgette N Kiethega, Marcel Turcotte, and Gertraud Burger. Evolutionarily Conserved cox1 Trans-Splicing Without cis-Motifs. Molecular biology and evolution, 28(9):2425–2428, September 2011.
  6. Mikhail Jiline, Stan Matwin, and Marcel Turcotte. Annotation Concept Synthesis and Enrichment Analysis: a Logic-Based Approach to the Interpretation of High-Throughput Experiments. Bioinformatics, 27(17):2391–2398, July 2011.
  7. A. Bellamy-Royds and M. Turcotte. Can clustal-style progressive pairwise alignment of multiple sequences be applied to RNA secondary structure prediction? BMC Bioinformatics, 8:190, 2007.
  8. V.X. Jin and M. Turcotte. Detecting localized interspersed motifs in genomic sequences: Application to the mouse genome. IEEE Transactions on Instrumentation and Measurement, 56(5):1770–1775, October 2007.
  9. S.D. Baird, S. M. Lewis, M. Turcotte, and M. Holcik. A search for structurally similar cellular internal ribosome entry sites. Nucl. Acids Res., 35(14):4664–4677, 2007.
  10. S.D. Baird, M. Turcotte, R. G. Korneluk, and M. Holcik. Searching for IRES. RNA Journal, 12(10):1755–1785, 2006.
  11. M. Anwar, T. Nguyen, and M. Turcotte. Identification of consensus RNA secondary structures using suffix arrays. BMC Bioinformatics, 7:244, 2006.
  12. B. Masoumi and M. Turcotte. Simultaneous alignment and structure prediction of three RNA sequences. International Journal of Bioinformatics Research and Applications, 1(2):230–245, 2005.
  13. M. Turcotte, S.H. Muggleton, and M.J.E. Sternberg. Generating protein three-dimensional fold signatures using inductive logic programming. Computers & Chemistry, 26(1):57–64, December 2001.
  14. M. Turcotte, S.H. Muggleton, and M.J.E. Sternberg. Automated discovery of structural signatures of protein fold and function. J. Mol. Biol., 306(3):591–605, 2001.
  15. M. Turcotte, S.H. Muggleton, and M.J.E. Sternberg. The effect of relational background knowledge on learning of protein three-dimensional fold signatures. Machine Learning, 43:81 – 95, 2001.
  16. M. Turcotte, S.H. Muggleton, and M.J.E. Sternberg. Use of inductive logic programming to learn principles of protein structure. Electronic Transactions on Artificial Intelligence, ETAI, 5(39), 2000.
  17. S.A. Benner, G. Cannarozzi, D. Gerloff, M. Turcotte, and G. Chelvanayagam. Bona Fide prediction of protein secondary structure using transparent analyses of multiple sequence alignments. Chemical Review, 97(8):2725 – 2843, 1997.
  18. D.L. Gerloff, F.E. Cohen, C. Korostensky, M. Turcotte, G.H. Gonnet, and S.A. Benner. A predicted concensus for the N-terminal fragment of the heat shock protein HSP90 family. Proteins: Struct. Funct. Genet., 27:450–458, 1996.
  19. M. Turcotte, G. Lapalme, and F. Major. Exploring the conformations of nucleic acids. J. Funct. Prog., 5(3):443–460, 1995.
  20. M. Feeley, M. Turcotte, and G. Lapalme. Using Multilisp for solving constraint satisfaction problems: an application to nucleic acid 3D structure determination. LISP AND SYMBOLIC COMPUTATION, 7(2/3):232–247, 1994.
  21. F. Major, M. Turcotte, , D. Gautheret, G. Lapalme, E. Fillion, and R. Cedergren. The combination of symbolic and numerical computation for three-dimensional modeling of RNA. Science, 253:1255–1260, September 1991.

Papers in referred conference proceedings

  1. Kevin Sutanto and Marcel Turcotte. Extracting and evaluating features from RNA virus sequences to predict host species susceptibility using deep learning. In 13th International Conference on Bioinformatics and Biomedical Technology (ICBBT 2021), Northwestern Polytechnical University, Xi’an, China, May 21-23 2021.
  2. Kevin Sutanto and Marcel Turcotte. Assessing the use of secondary structure fingerprints and deep learning to classify RNA sequences. In IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Seoul, South Korea, December 16-19 2020.
  3. Manuel Belmadani and Marcel Turcotte. MotifGP: Using multi-objective evolutionary computing for mining network expressions in DNA sequences. In IEEE International Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB 2016), Chiang Mai, Thailand, October, 5-7, 2016 2016.
  4. Isra Al-Turaiki, Ghada Badr, Marcel Turcotte, and Hassan Mathkour. Incremental structural motif discovery. In International Symposium on Bioinformatics Research and Applications (ISBRA), 2013.
  5. Alexander Gawronski and Marcel Turcotte. Novel framework for the discovery of RNA elements and its application to Euglenozoa. In International Symposium on Bioinformatics Research and Applications (ISBRA), 2013.
  6. Oksana Korol and Marcel Turcotte. Learning relationships between over-represented motifs in a set of DNA sequences. In CIBCB 2012 : IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, San Diego, USA, May 9–12 2012.
  7. Sandrine Moreira, Marcel Turcotte, and Gertraud Burger. NGS: Neglected genome sequencing assembly and annotation challenges in a highly divergent protozoan genome. In JOBIM 2011 : Journées Ouvertes en Biologie, Informatique et Mathématiques, Paris, France, June 28 – July 1 2011.
  8. Ghada Badr and Marcel Turcotte. Component-based matching for multiple interacting rna sequences. In Jianer Chen, Jianxin Wang, and Alexander Zelikovsky, editors, Bioinformatics Research and Applications, volume 6674 of Lecture Notes in Computer Science, pages 73–86. Springer Berlin / Heidelberg, 2011. 10.1007/978-3-642-21260-4_11.
  9. Mikhail Jiline, Stan Matwin, and Marcel Turcotte. Annotation concept synthesis and enrichment analysis: a logic-based approach to interpretation of high-throughput experiments. In A. Farzindar and V. Keselj, editors, Canadian Conference on Artificial Intelligence 2010, Lecture Notes in Artificial Intelligence 6085, pages 304–308, Ottawa, May 31–June 2 2010.
  10. Étienne Ogoubi, David Pouliot, M. Turcotte, and Abdelhakim Hafid. Parallel multiprocessor approaches to the RNA folding problem. In Parallel Processing and Applied Mathematics, pages 1230–1239, 2008.
  11. Étienne Ogoubi, Abdelhakim Hafid, and M. Turcotte. An Isometric on on-Chip Multiprocessor Architecture. In Electronics, Circuits and Systems, 2007. ICECS 2007. 14th IEEE International Conference on, pages 991–994, December 11–14, 2007 2007.
  12. M. Anwar and M. Turcotte. An approach to selecting putative RNA motifs using MDL principle. In BIOCOMP’06 — The 2006 International Conference on Bioinformatics & Computational Biology, pages 560–565, Las Vegas, Nevada, USA, June 26–29 2006.
  13. M. Anwar and M. Turcotte. Evaluation of RNA secondary structure motifs using regression analysis. In IEEE CCECE 2006 — Canadian Conference on Electrical and Computer Engineering, pages 1716–1721, Ottawa, Canada, May 7–10 2006.
  14. T. Nguyen and M. Turcotte. Exploring the space of RNA secondary structure motifs using suffix arrays. In S. Blair et al., editor, 6th International Symposium on Computational Biology and Genome Informatics (CBGI 2005), pages 1291–1298, Salt Lake City, Utah, USA, July 21-26 2005.
  15. B. Masoumi and M. Turcotte. Simultaneous alignment and structure prediction of RNAs: Are three input sequences better than two? In V.S. Sunderam, G.D. van Albada, P.M.A. Sloot, and J. Dongarra, editors, 2005 International Conference on Computational Science (ICCS 2005), Lecture Notes in Computer Science 3515, pages 936–943, Atlanta, USA, May 22-25 2005.
  16. V. Jin and M. Turcotte. Detecting localized interspersed motifs in genomic sequences. In IMTC/05 IEEE Instrumentation and Measurement Technology Conference, pages 267–270, Ottawa, Canada, May 17-19 2005.
  17. M. Turcotte, S.H. Muggleton, and M.J.E. Sternberg. Application of inductive logic programming to discover rules governing the three-dimensional topology of protein structure. In C. D. Page, editor, Proc. of the 8th International Workshop on Inductive Logic Programming (ILP-98), Lecture Notes in Artificial Intelligence 1446, pages 53–64, Berlin, 1998. Springer-Verlag.

Abstracts and/or papers read

  1. Aseel Awdeh, Marcel Turcotte, and Theodore J. Perkins. Cell type specific binding preferences of transcription factors. In Great Lakes Bioinformatics Conference, GLBIO 2021, May 10–13 2021.
  2. Aseel Awdeh, Marcel Turcotte, and Theodore J. Perkins. WACS: Improving peak calling by optimally weighting controls. In Great Lakes Bioinformatics Conference, GLBIO 2019, May 19–22 2019.
  3. Andrew Sowinski, Marcel Turcotte, Gilbert Arbez, and David Taylor. One-minute quizzes to identify potential students atc risk in engineering courses. In Proceedings of the Canadian Engineering Education Association (CEEA), University of Toronto, June 4–7 2017.
  4. Mikhail Jiline, Stan Matwin, and Marcel Turcotte. Annotation concept synthesis and enrichment analysis: A logic-based approach to the interpretation of high-throughput biological experiments. In 2012 Learning Workshop, Snowbird, Utah, April 3-6 2012. Computational and Biological Learning Society and the NIPS.
  5. S. Moreira, S. Breton, M. Valach, M. Aoulad Aissa, M Turcotte, and G Burger. Identification of an elusive trans-splicing machinery. In Annual meeting of the Society for Molecular Biology & Evolution (SMBE 2012), Dublin, Ireland, June 23-26 2012. Poster.
  6. Sandrine Moreira, Marcel Turcotte, and Gertraud Burger. In silico identification of the elusive trans-splicing machinery of a highly divergent protozoan. In 2011 MonBUG Bioinformatics Symposium, Montréal, September 23 2011.
  7. Sandrine Moreira, Marcel Turcotte, and Gertraud Burger. Diversité géomique : le curieux mode d’expression des gènes d’un eucaryote unicellulaire. In Association francophone pour le savoir (ACFAS), Sherbrooke, Canada, May 9–13 2011.
  8. Georgette Kiethega, Marcel Turcotte, and Gertraud Burger. Nouveau mécanisme de trans-splicing dans la mitochondrie des diplon´m ides. In Association francophone pour le savoir (ACFAS), Sherbrooke, Canada, May 9–13 2011.
  9. Oksana Korol and Marcel Turcotte. Mining for relationships between biological markers in high-throughput sequence data. In 2011 MonBUG Bioinformatics Symposium, Montréal, September 23 2011.
  10. Gertraud Burger, Georgette Kiethega, and Marcel Turcotte. Unconventional trans-splicing and RNA-editing in mitochondria of an Euglenozoan. In ICPMB 2011. International Conference for Plant Mitochondrial Biology, Hohenroda, Germany, May 14–19 2011.
  11. Oksana Korol and Marcel Turcotte. Module Inducer — a tool to automatically extract knowledge from biological sequences. In RECOMB2011, 15th Annual International Conference of Research in Computational Molecular Biology, Vancouver, March 28–31 2011.
  12. Yifei Yan, Seyed Amir Malekpour, Marcel Turcotte, Georgette Kiethega, and Gertraud Burger. RNA editing and trans-splicing directed by gRNAs? In 2011 Gordon Research Conference on RNA Editing, January 9–14 2011. Poster.
  13. Sandrine Moreira, Marcel Turcotte, and Gertraud Burger. Analysis of potential nuclear RNA editing sites in a highly divergent protozoa. In 2010 Robert Cedergren Bioinformatics Colloquium, 2010.
  14. Seyed Amir Malekpour, Marcel Turcotte, and Gertraud Burger. gRNA mediated trans-splicing of gene modules in diplonema papillatum. In 2010 Robert Cedergren Bioinformatics Colloquium, 2010.
  15. Georgette Kiethega, Marcel Turcotte, and Gertraud Burger. cox1 gene fragmentation and rna editing in diplonemid mitochondria. In 18th meeting of International Society for Evolutionary Protistrogy (ISEP XVIII), Kanazawa, Japan, July 2–7 2010 2010.
  16. S. Kannan, M. Turcotte, and M. Burger. Automated (RNA) motifs discovery in the mitochondrial genome of diplonema papillatum. Oral presentation, Robert Cedergren Bioinformatics Colloquium 2008, Montréal, Canada, 2008.
  17. M. Jiline, K. Baetz, M. Turcotte, and S. Matwin. Knowledge enriched mining of systematic genome screens using inductive logic programming. In Progress in Systems Biology 2006, Ottawa, November 9 and 10 2006. Oral presentation.
  18. S. Baird, M. Turcotte, R. Korneluk, and M. Holcik. Discovery of novel internal ribosome entry site motifs from searches with the XIAP IRES structure. 2006 Cold Spring Harbor Laboratory Meeting on Translational Control, Poster, September 6 – 10 2006.
  19. S. Baird, M. Turcotte, R. Korneluk, and Holcik M. Searching for IRES structurally similar to the XIAP IRES. In RNA 2005, the Tenth Annual Meeting of the RNA Society, Banff, Canada. Poster #566, May 24-29 2005.
  20. S. Baird, M. Turcotte, R. Korneluk, and Holcik M. Searching for IRES. CIHR National Student Research Poster Competition, Winnipeg, Canada, Poster Session, June 7-8 2005.
  21. B. Masoumi and M. Turcotte. A dynamic programming algorithm for [the] simultaneous alignment and structure prediction of 3 RNA sequences. BioNorth 2004 — 11th Annual Ottawa Life Sciences International Conference & Exhibition, Poster #114, Nov 29-Dec 1st 2004.
  22. S. Baird, M. Turcotte, R. Korneluk, and Holcik M. Structural determination of internal ribosome entry sites with currently available software. In RNA 2004, the Ninth Annual Meeting of the RNA Society, Madison, Wisconsin, Poster Session, June 1-6 2004.
  23. S. Baird, M. Turcotte, R. Korneluk, and M. Holcik. Searching for IRES. In The Canadian Genetic Diseases Network Annual Scientific Meeting, Kimberly, Ontario, Poster Session, May 27-30 2004.
  24. M. Turcotte. Détermination de structures secondaires conservées dans les ARNs: Application à l’étude des transcrits du gène c-myc des mammifères. 72e congrès de l’ACFAS, Montréal, Canada, May 10-14 2004. Oral Presentation.
  25. S. Baird, S. Balabanian, R. G. Korneluk, M. Turcotte, and M. Holcik. Unique sequence characteristics of internal ribosome entry sites useful for database search. BioNorth 2002 — 9th Annual Ottawa Life Sciences International Conference & Exhibition, Poster session, November 4–6 2002.
  26. M. Turcotte. Automatic discovery of structural motifs. First Canadian Working Conference on Computational Biology (CCCB’00), November 12 2000. Oral Presentation.
  27. M. Turcotte, S.H. Muggleton, and M.J.E. Sternberg. Generating protein three-dimensional folds signatures using inductive logic programming. In 2000 Convention of the Society for the Study of Artificial Intelligence and the Simulation of Behaviour, Birmingham, UK, April 17-20 2000. Oral Presentation.
  28. M. Turcotte, S.H. Muggleton, and M.J.E. Sternberg. Learning protein structure principles. In The 17th Machine Intelligence Workshop, Suffolk, UK, July 19-21 2000. Oral Presentation.
  29. M. J. E. Sternberg, P. A. Bates, L. A. Kelley, R. M. MacCallum, A. Müller, S. Muggleton, and M. Turcotte. Exploiting protein structure in the post-genome era. In Intelligent Systems for Molecular Biology 1999, 1999. Oral Presentation.
  30. M. Turcotte, S.H. Muggleton, and M.J.E. Sternberg. Learning rules which relate local structure to specific protein taxonomic classes. In The 16th Machine Intelligent Workshop, King’s Manor, York, December 1–3 1998.
  31. M. Turcotte, S.H. Muggleton, and M.J.E. Sternberg. A Prolog database unifying taxonomic and structural information. In Intelligent Systems for Molecular Biology (ISMB 1998) Book of Abstracts, Poster Session, Montréal, Canada, June 28–July 1 1998.
  32. M. Turcotte and M. Feeley. A parallel functional program for searching a discrete space of nucleic acid 3d structures. In Dagstuhl-Seminar, Germany, 1994. Oral Presentation.
  33. F. Major, M. Turcotte, and G. Lapalme. Constraint satisfaction in functional programming. In Principles and Practice of Constraint Programming, pages 174–177, Newport, Rhode Island, April 28–30 1993.
  34. M. Turcotte, G. Lapalme, and R. Cedergren. A measure of association for coordinated substitutions in proteins. In Book of Abstracts, Patterns of Biological Organizations, Rensselaerville, NY, October 1992. 1992 Albany Conference. Poster Session.
  35. D. Gautheret, M. Turcotte, R. Cedergren, F. Major, and G. Lapalme. Modeling and prediction of RNA 3-D structures by combining symbolic and numerical approaches. J. Biomol. Struct. Dynam., 8(6):a061, June 1991.
  36. R. Cedergren, F. Major, D. Gautheret, E. Fillion, L. Jolicoeur, M. Turcotte, and R. Cedergren. A 3-D model of the hammerhead domain derived from experimental and topological constrainsts. International Conference on Catalytic RNA as Anti-HIV agent: Design and Delivery to Cells, San Diego, California, October 1990. Oral Presentation.
  37. M. Turcotte, F. Major, G. Lapalme, D. Gautheret, E. Fillion, and R. Cedergren. Using functional and logic programming in molecular graphics applications. 9th annual meeting of the Molecular Graphics Society, helded Uppsala, Sweeden, Poster Session, July 1990.
  38. M. Turcotte, G. Lapalme, R. Cedergren, and F. Major. A user-interface for the folding and unfolding system (FUS). 1st C.I.A.R. Evolution Group Meeing for Graduate Students, Université de Montréal, Montréal, Canada, Oral Presentation, 1989.

Supervision: current

Amirhossein Hajianpour

Master of Computer Science (M.C.S.) Specialization in Bioinformatics
ExonHunter (EH): Simple and Fast Homology-based Gene Prediction in Mitochondrial Genomes
2018-Present

Bhagya Chattanahalli Thimmappa

Philosophiae doctor (Ph.D.) in Bioinformatics
Plant growth-promoting potential of an endophyte isolated from Cranberry plant.

Primary supervisor: Gertraud Burger, Université de Montréal

2018-Present

Aseel Awdeh

Philosophiae doctor (Ph.D.) in Computer Science
WACS: Improving ChIP-seq peak calling by optimally weighting controls. Cell type specific binding preferences of transcription factors.

Primary supervisor: Theodore J. Perkins, Ottawa Hospital Research Institute

2015-Present
Supervision: alumni

Kevin Sutanto

Master of Computer Science (M.C.S.) Specialization in Bioinformatics
RNA Sequence Classification using Secondary Structure Fingerprints, Sequence-Based Features, and Deep Learning. Like proteins, functional RNAs are able to fold into complex structures in order to perform specific functions throughout their lifecycle. We hypothesized that using a representation that includes the multiple possible secondary structures of an RNA for classification purposes may improve the classification performance.

Permalink: http://hdl.handle.net/10393/41876

2019-2021

Sandrine Moreira Rousseau

Philosophiae doctor (Ph.D.) in Bioinformatics
Discovery of new strategies for encrypting genetic information in eukaryotes, and the identification of molecular decoding processes in a group of poorly studied marine protists, the Diplonemids.

Primary supervisor: Gertraud Burger, Université de Montréal
Permalink: http://hdl.handle.net/1866/18548

2010-2016

Manuel Belmadani

MASTER OF COMPUTER SCIENCE (M.C.S.) SPECIALIZATION IN BIOINFORMATICS
MotifGP is a multiobjective motif discovery tool evolving regular expressions that characterize overrepresented motifs in a given input dataset. This thesis describes and evaluates a multiobjective strongly typed genetic programming algorithm for the discovery of network expressions in DNA sequences.

Permalink: http://hdl.handle.net/10393/34213

2012-2016

Julien Horwood

Undergraduate Student Summer Internship
Python implementation of Fast Text Searching for Regular Expressions on Tries
2015

Aseel Awdeh

MASTER OF COMPUTER SCIENCE (M.C.S.) SPECIALIZATION IN BIOINFORMATICS
Inferring regulatory relationships between genes, including the direction and the nature of influence between them, is the foremost problem in the field of genetics. The thesis explores the possibility of dynamic epistasis analysis.

Primary supervisor: Theodore J. Perkins, Ottawa Hospital Research Institute
Permalink: http://hdl.handle.net/10393/32747

2013-2015

Alexander Gawronski

MASTER OF COMPUTER SCIENCE (M.C.S.) SPECIALIZATION IN BIOINFORMATICS
Frequent subgraph mining is a useful method for extracting biologically relevant patterns from a set of graphs or a single large graph. In this thesis, the graph represents all possible RNA structures and interactions. The algorithm was applied to the mitochondrial genome of the kinetoplastid species Trypanosoma brucei.

Permalink: http://hdl.handle.net/10393/26296

2011-2013

Victor Hugo Sperle Campos

Undergraduate International Student from Brazil Internship
Multiple Protein Sequence Alignment, Tree Length, Median String Problem, Asymmetrical Substitution Score.
2013

Oksana Korol

MASTER OF COMPUTER SCIENCE (M.C.S.) SPECIALIZATION IN BIOINFORMATICS
An approach aimed at discovering patterns in a set of DNA sequences based on the location of transcription factor binding sites or any other biological markers with the emphasis of discovering relationships. A variety of statistical and computational methods exists to analyze such data. However, they either require an initial hypothesis, which is later tested, or classify the data based on its attributes. This approach does not require an initial hypothesis and the classification it produces is based on the relationships between attributes.

Permalink: http://hdl.handle.net/10393/20320

2009-2011

Etienne Elie

Philosophiae doctor (Ph.D.) in Computer Science
Approche efficace pour la conception des architectures multiprocesseurs sur puce électronique. Nous nous intéressons à un modèle architectural, appelé architecture isométrique de systèmes multiprocesseurs sur puce, qui permet d'évaluer, de prédire et d'optimiser les systèmes OCM en misant sur une organisation efficace des nœuds (processeurs et mémoires), et à des méthodologies qui permettent d'utiliser efficacement ces architectures.

Primary supervisor: Abedl Hakim Hafid, Université de Montréal
Co-supervisor: Jacques Ferland, Université de Montréal
Permalink: http://hdl.handle.net/1866/6841

2006-2011

Mikhail (Misha) Jiline

Philosophiae doctor (Ph.D.) in Computer Science
The thesis proposes a novel logic-based Annotation Concept Synthesis and Enrichment Analysis (ACSEA) approach. In this approach, the source annotation information, experimental data and uncovered enriched annotations are represented as First-Order Logic (FOL) statements.

Primary supervisor: Stan Matwin, Dalhousie University
Permalink: http://hdl.handle.net/10393/19712

2006-2010

Ghada Badr

Postdoctoral Fellow
We proposed two algorithms for locating all the occurrences of a given interaction pattern in a set of RNA sequences. The baseline algorithm implements an exhaustive backtracking search. The second algorithm also finds all the matches, but uses additional data structures in order to considerably decrease the execution time, sometimes by one order of magnitude.
2009-2011

Predrag Mizdrak

Master of Computer Science (M.C.S.)
Multiple sequence alignment (MSA) and phylogeny tree reconstruction are two imporant problems in bioinformatics. In some respect, they represent "two sides of the same coin", since solving either of the two problems would be easier if the solution to the other problem was given. The thesis proposes a new method that addresses these shortcomings by iteratively improving the starting alignment and its corresponding evolutionary tree based on maximum likelihood scores.

Co-supervisor: Stéphane Aris-Brosou
Permalink: http://hdl.handle.net/10393/28253

2008-2009

Sivakumar Kannan

Postdoctoral Fellow
RNA sequence and structure motif discovery in Diplonema papillatum.

Primary supervisor: Gertraud Burger, Université de Montréal

2008

Stephen Baird

Philosophiae doctor (Ph.D.) in Microbiology and Immunology Specialization in Human and Molecular Genetics
The standard method of translation initiation, where the ribosome binding onto mRNA is mediated by initiation factors that congregate at the 5' "cap-nucleotide" of the RNA, is at times, partially disabled. For example, during viral infection, mitosis, and cellular stress, the efficiency of this form of initiation is reduced relative to an alternate mechanism of initiation that utilizes Internal Ribosome Entry Sites (IRESes) contained in the 5' UTR sequence of viral and cellular RNA transcripts. The thesis investigates the structure of cellular IRES.

Primary supervisor: Robert Korneluk
Cosupervisor: Martin Holcik
Permalink: http://hdl.handle.net/10393/29386

2000-2006

Amelia Bellamy-Royds

Undergraduate Student Summer Internship
Progressive simultaneous alignment and structure prediction of multiple RNA sequences. The research presented here investigates the possibility of applying a progressive, pairwise approach to the alignment of multiple RNA sequences by simultaneously predicting an energy-optimized consensus secondary structure. We take an existing algorithm for finding the secondary structure common to two RNA sequences, Dynalign, and alter it to align profiles of multiple sequences. We then explore the relative successes of different approaches to designing the tree that will guide progressive alignments of sequence profiles to create a multiple alignment and prediction of conserved structure.

PubMed ID: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1904245/

2006

Mohammad Anwar

Master of Computer Science (M.C.S.)
Implementation and evaluation of scoring schemes for the automated discovery of nucleic acid structures. Extends the work of Nguyen (M.A.Sc thesis, Electrical Engineering, University of Ottawa, 2004) who introduced a novel approach for discovering consensus secondary structure motifs in a set of unaligned RNA sequences. The algorithm has been implemented in a software system called Seed. The aim of this thesis is to devise, implement and evaluate (3) scoring schemes for the software system.

Permalink: http://hdl.handle.net/10393/27220

2004-2006

Mohak Shah

Philosophiae doctor (Ph.D.) in Computer Science
Sample compression, margins and generalization: Extensions to the set covering machine. This thesis studies the generalization behavior of algorithms in Sample Compression Settings. It extends the study of the Sample Compression framework to derive data-dependent bounds that give tighter guarantees to the algorithms where data-independent bounds such as the VC bounds are not applicable.

Primary supervisor: Mario Marchand, Université Laval
Permalink: http://hdl.handle.net/10393/29372

2004-2006

Beeta Masoumi

Master of Computer Science (M.C.S.)
Simultaneous alignment and structure prediction for three ribonucleic acid sequences. Using more input sequences should improve the accuracy, reduce the likelihood that bad predictions are made, but also lower the sensitivity. To investigate these claims, we have extended the software system Dynalign to use three input sequences, rather than two, and tested our algorithm with 10 tRNAs and 13 5S rRNAs.

Permalink: http://hdl.handle.net/10393/26974

2003-2005

Truong Nguyen

Master of Applied Science (M.A.Sc.) in Electrical Engineering
Transcription and translation are critical steps through which genetic expression occurs. Whereas there exists research for computationally determining the primary structure binding sites for transcription, research into the computational elucidation of secondary structure binding sites for translation has not been as thoroughly conducted. The approach proposed involves first selecting a single sequence from a set of data sequences. From this sequence, all biological palindromes are determined. Using these palindromes, all possible candidate secondary structure motifs with minimum support are assembled, formulating the solution space. The motifs in the solution space are reduced to structural form. These structures are searched against the remaining sequences.

Permalink: http://hdl.handle.net/10393/26727

2002-2004

Chunfang Zheng

NSERC Undergraduate Student Research Awards (USRA)
Covariation analyses for the study of protein contacts.
2003

Victor Jin

Master of Computer Science (M.C.S.)
A Computational Approach to the Analysis of Localized Interspersed Motifs in Complete Genomic Sequences.
2000-2003

Teaching

ITI 1121 - Introduction to Computing II

Object-oriented programming. Abstraction principles: information hiding and encapsulation. Linked lists, stacks, queues, binary search trees. Iterative and recursive processing of data structures. Virtual machines.

(Winter 2002-08, 10-11, 13-15, 18-20)
ITI 1521 - Introduction à l'informatique II

Programmation orientée objet. Principes d'abstraction: masquage et encapsulation. Listes chaînées, piles, files, arbres de recherche binaires. Traitement itératif et récursif des structures de données. Machines virtuelles.

(Hiver 2001, 03-08, 10-12, 16-20)
CSI 5180 - Machine Learning for Bioinformatics Applications

Machine learning theories and methods with applications to biological sequence data, gene expression, genomics and proteomics.

(Fall 2019)
BNF 5106 (BIOL 5515) - Bioinformatics, RNA Bioinformatics lecture

Major concepts and methods of bioinformatics. Topics may include, but are not limited to: genetics, statistics & probability theory, alignments, phylogenetics, genomics, data mining, protein structure, cell simulation and computing.

(Fall 2007-16, 18-19)
CSI 5126 (COMP 5108) - Algorithms in bioinformatics

Fundamental mathematical and algorithmic concepts underlying computational molecular biology; physical and genetic mapping, sequence analysis (including alignment and probabilistic models), genomic rearrangement, phylogenetic inference, computational proteomics and systemics modelling of the whole cell.

(Fall 2000-03, 05-07, 09, 16-18)
CSI 3540 - Structures, techniques et normes du Web

Infrastructure de base du Web. Serveurs et navigateurs. Exemples de protocoles. Internet et virus. Architecture de moteur de recherche. Contenu et présentation Web. Pages Web, leur structure et leur interprétation. HTML, XML et leurs dérivés. Interfaces Web vers les logiciels et bases de données. Témoins et droit à la vie privé. Web sémantique et ontologies. Services Web.

(Hiver 2008, 10)
BCH/CMM 8310 - Current topics in RNA molecular biology, RNA lecture

Properties, mechanisms associated with regulation and the function of RNAs and Ribonucleoprotein (RNPs) as well as RNA organisms. Current knowledge on RNA expression (synthesis, processing, transport and localization), the structure-function relationship and molecular mechanisms associated with RNAs and RNA genomes, RNA in evolution and in the origin of life, and RNA as therapeutic agents. Courses BCH 8310 and CMM 8310 cannot be combined for units.

(Fall 2007-10)
CSI 4900 - Projects

Un projet d'une durée d'un semestre, à faire seul ou en petit groupe, sous la supervision d'un professeur. Les projets sont affichés et sont choisis durant le semestre précédent. Les étudiants doivent participer aux présentations des projets, cédulées à la fin du semestre. / A one-semester project, individual or for a small group, carried out under the supervision of a faculty member. Projects are posted and selected in the preceding semester. The students are required to participate in project presentations scheduled at the end of the semester.


Contact

University of Ottawa Logo

Marcel Turcotte, Ph.D.

Computer Science Professor

School of Electrical Engineering and Computer Science (EECS)
Faculty of Engineering
University of Ottawa