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Dan Tulpan


Position/Title: Assistant Professor
email: dtulpan@uoguelph.ca
Phone: (519) 824-4120 ext. 52482
Office: ANNU 127

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Dan Tulpan’s research interests range from computational biology and bioinformatics to mathematical modelling and computer vision (using computers to extract and process data from images).  His expertise has application across a broad range of topics, but at U of G, Dan is applying his skills to livestock breeding and other areas of plant and animal science.  Previously, Dan was a research officer in the Scientific Data Mining Team, Digital Technologies Research Center of the National Research Council in Moncton, New Brunswick.  There, he headed the NRC Atlantic Bioinformatics Laboratory. He has held numerous research and academic positions across Canada and worked in the software industry internationally.

Academic history

  • Postdoctoral Fellow, Simon Fraser University, Department of Molecular Biology and Biochemistry, 2006-2007
  • Ph.D., University of British Columbia, Department of Computer Science, 2000-2006
  • B.Sc./B.Eng., Politechnic University of Bucharest, Department of Engineering Sciences and Computers, 1995-2000

Affiliations and Partnerships

  • Adjunct Professor, School of Computer Science, University of Guelph
  • Association of Computing Machinery (ACM)

Selected Awards and Honours

Research Impact

Dan is relatively new to U of G, and he’s enthused about building an innovative research program. His focus will be on advanced computing and information technology to provide solutions to challenges in animal agriculture such as automatic animal identification, tracking and phenotype acquisition. He has published over 50 peer-reviewed articles, edited a book, co-authored scientific software for computational biology and bioinformatics and contributed to the formation of several highly qualified personnel such as students and programmers. Dan serves on several international conferences and journal editorial boards, co-organizes the ACM Symposium of Applied Computing Track on Bioinformatics and maintains strong research collaboration with researchers in Italy, Switzerland, Spain and other countries.

Research Themes and Projects

  • Theme 1: Development of an automatic real-time data acquisition platform for phenomics, physiological and environment information for livestock and poultry. The platform should be capable to capture and store information in real-time and periodically based on a variety of on-animal (e.g. accelerometers, magnetometers, gyroscopes, visual, audio, location), off-animal (e.g. cameras, thermal imaging, walk-over scales, LIDAR lasers) and/or in-animal (e.g. RFID chips) sensors. Ideally, the platform will be able to interface with existing acquisition systems developed by other research groups.

Projects TBA

  • Theme 2: Development of bioinformatics and computer vision data integration pipelines capable to efficiently select, filter, model and process the acquired information. The original data will be transformed into ready-to-analyze information and will be combined when needed with complementary external information resources (e.g. environment data, GPS locations, maps, other omics sources)

Projects TBA

  • Theme 3: Development of real-time interactive analytic and visualization tools to turn high-throughput phenomics data into testable hypotheses and actionable results and facilitate genotype-phenotype association studies.

Projects TBA

(Under)Graduate Student Information

Dan’s research is truly interdisciplinary and has a strong bioinformatics and biology component. Therefore, graduate students should have good computing skills and be keenly interested in learning new tools and applying their knowledge to biological problems. Supervising, mentoring, guiding and working with talented, hard working students is a passion for Dan and he is enthused about helping students reach their research potential and expand their knowledge with each project they contribute to.

Featured Publications

For a more comprehensive list of publications please visit Dr. Tulpan's Google Scholar page.

Featured Bioinformatics Software and Data Sets