Biomedical Informatics

Transforming how health care is approached and delivered through big data is the goal of our two new professional programs: a graduate diploma and a master's in Biomedical Informatics.

Using a ladder approach, students can take the 4 month graduate diploma, with the option to continue on to complete a one-year masters. Skills to be gained in these programs will provide hands-on training in data science that will form the foundation for successful careers in health care and biomedical research. Given the current abundance of data, knowledge and experience in data analytics is in high demand among health care professionals and researchers. Whether you are interested in pursuing careers in genetics, pharmaceuticals, medicine, or biomedical research, understanding how to manipulate and use large datasets is essential for translating data into knowledge that will undoubted transform health care.

Innovative in design, offered in partnership by the School of Computing and the Department of Biomedical and Molecular Sciences (DBMS), students will succeed through the hands-on and applied nature of the program. These programs are focused on training future data scientists who have a foundation in biology, life sciences, biochemistry, medical sciences and related disciplines in methods for database design and management, statistical analysis, data mining, and image analysis.

We would love to tell you more about it...
introduce yourself

Details about the Graduate Diploma

Timeline
May - August

Fees
$10,000 CDN

Delivery
on campus

Courses
The diploma consists of 4, 3-credit units including a final paper for CISC-897. The courses are:

  • CISC-897* (3 credit units) – Research Methods in Computer Science
  • CISC-801* (3 credit units) – Programming Skills and Tools for Processing of Biomedical Data
  • CISC-802* (3 credit units) – Biomedical Data Analysis
  • CISC-803* (3 credit units) – Data Mining and Applications

Details about the Master's Program (MBI)

Timeline
May - August

Fees
$20,000 CDN

Delivery
on campus

Courses
Students in the Diploma program will be permitted to ladder coursework successfully completed within the Diploma program into the Professional Master’s program. The program will consist of:

  • The equivalent of 24 credit unit courses, including those from the Graduate Diploma Program (12CU) as well as advanced courses in computing, biology and health science.
  • CISC 898 Master’s Project (6CU). A biomedical informatics project is undertaken under the supervision of a School member. The presentation of a seminar to describe the project is required.
  • Two additional 3 credit unit courses from a list of elective courses presented below (total: 6CU).

Elective course options include:

  • CISC-832 Data Base Management Systems
  • CISC-859 Pattern Recognition
  • CISC-873 Data Mining
  • CISC-881 Bioinformatics
  • CISC-886 Cloud Computing
  • BMED-809 Principle of Drug Discovery and Development
  • BMED-810 Protein Structure and Function
  • BMED-811 Advanced Molecular Biology
  • BMED-813 Advances in Neuropharmacology
  • BMED-815 Mechanistic Toxicology
  • BMED-854 Cardiovascular Sciences

Program Professors and Faculty

DBMS and the School of Computing are partnering in the development of these graduate programs in Biomedical Informatics. These opportunities will fill gaps in training highly qualified personnel with the skill set to apply computer science to multiple biological and medical datasets, including genomics and imaging, to uncover, understand and integrate biological relationships to better understand the biology underlying human diseases or traits such as drug response.

Core faculty from Computing include:
Dr. Qingling Duan (Queen’s National Scholar in Bioinformatics) is jointly appointed to the Department of Biomedical and Molecular Sciences and the School of Computing
Randy Ellis
(Queen’s Research Chair in Computer-Aided Surgery)
Gabor Fitchtinger (Cancer Care Ontario Research Chair)
Janice Glasgow (Queen’s Research Chair in Biomedical Computing)
Parvin Mousavi (Medical Informatics Lab)
James Stewart (Computer Assisted Mosaic Arthroplasty (CAMA))
Selim Akl (Parallel and Unconventional Computation Group)
Dorothea Blostein (Biomechanics and Adaptive Tensegrity)

The School of Computing is currently a leader in Biomedical Computing, offering a unique undergraduate program in the field and carrying out world-class research in the areas of bioinformatics, computer-aided surgery, medical imaging, computer-assisted intervention, medical diagnosis, drug discovery, and computational neuroscience. External collaborations include researchers at the National Institute of Health (USA), Harvard University, John Hopkins University, Medialo University of Vienna, University of British Columbia, Western University, Princess Margaret Hospital (Toronto), and others. In addition, the School of Computing has experts in such related areas as big-data analysis (Pat Martin) and data mining (David Skillicorn).

 

Core faculty from DBMS will include:
Dr. Qingling Duan (Queen’s National Scholar in Bioinformatics) is jointly appointed to the Department of Biomedical and Molecular Sciences and the School of Computing
Michael Adams
(Head of the Department)
James Reynolds
Gunnar Blohm
Christopher Mueller
Louise Winn

DBMS is a distinguished academic centre engaged in a wide range of research endeavours including anatomical sciences, bacteriology, biochemistry, cancer biology, cardiovascular sciences, cell biology, developmental biology, immunology, molecular biology, genomics, neuroscience, pharmacology, physiology, reproductive biology, toxicology and virology. The breadth and depth of research has a strong foundation in multi-disciplinary discovery. Prominent in this regard are the educational efforts in the highly regarded Life Sciences and Biochemistry undergraduate programs, in medical education and in stellar graduate program. 

Course Descriptions

CISC-897* Research Methods in Computer Science (3CU)
This course provides an introduction to the primary and secondary sources of information in the computing science literature. The course includes work aimed at improving research skills. Students are required to submit and present a paper on a topic that relates to their research.

CISC-801* Programming Skills and Tools for Processing Biomedical Data (3CU)
The objective of this course is to provide graduating health science students hands-on training in computer programming languages and tools to familiarize them with the principles and practice of cutting edge technologies for bioinformatics used in biomedical and molecular sciences research.

CISC-802* Biomedical Data Analysis (3CU)
The objective of this course is to provide graduating health science students hands-on training in the analysis of biomedical datasets to familiarize them with the principles and practice of cutting edge technologies for bioinformatics used in biomedical and molecular sciences research.

CISC-803* Data Mining and Applications (3CU)
The objective of this course is to provide graduating health science students with hands-on training in data mining to familiarize them with the principles and practice of cutting edge technologies for bioinformatics used in biomedical and molecular sciences research. 

CISC-898 Master's Project (6CU)
A major programming project is undertaken under the supervision of a School member. The presentation of a seminar to describe the project is required.

CISC-832* Data Base Management Systems (3CU)
Theory and practice of modern data base systems; data as a model of reality; architecture of current and proposed systems. Networks models, entity data model and relational models of data. Data independence, security, data base integrity, contention handling, data definition languages, data manipulation languages and their relation to current and proposed systems. Readings from current research literature. Two term-hours; lectures. Two term-hours; lectures.

CISC-859* Pattern Recognition (3CU)
An introduction to statistical and structural pattern recognition. Feature extraction and the feature space. Bayes decision theory. Parametric classification. Clustering methods. Syntactic pattern description: string, tree and graph grammers; attributed grammars; stochastic grammars. Error correcting parsing; parsing of stochastic languages. Assignments include practical experience in application areas such as character recognition and document image analysis. Three term-hours; lectures and seminars.

CISC-873* Data Mining (3CU)
Study of the extraction of concepts from large high-dimensional datasets. Statistical foundations; techniques such as supervised neural networks, unsupervised neural networks, decision trees, association rules, Bayesian classifiers, inductive logic programming, genetic algorithms, singular value decomposition, hierarchical clustering. Three term hours; lectures and seminars.

CISC-881* Bioinformatics (3CU)
This inter-disciplinary course for students in the computational and life sciences looks at the application of computing techniques to molecular biology. Topics may include: DNA data analysis (genomics), secondary and tertiary structure analysis (nucleic acids and proteins), molecular scene analysis, evolutionary trees (phylogenetics), and computing with DNA. Three term hours; lectures and seminars. EXCLUSION: Jointly with BCHM-875*.

CISC-886* Cloud Computing (3CU)
Cloud computing is a distributed computing paradigm where computing resources are provided in an on-demand manner. The goal of the courses is to introduce students to key concepts and techniques from cloud computing. The course focuses on issues such as system architectures, resource allocation and management, and approaches and systems for the storage, management and processing of data in cloud environments.

BMED-809* Principles of Drug Discovery and Development (3CU)
An advanced course in which various aspects of the drug discovery and development process, from molecules to community, will be studied. The course comprises lectures, discussion and student seminars, based on recent literature. Topics encompass medicinal chemistry approaches to drug discovery, receptor theory, mechanisms of drug action, drug metabolism, pharmacokinetics, pharmacogenetics, drug resistance, clinical trials, and regulatory affairs. 3 hour seminar.

BMED-810* Protein Structure and Function (3CU)
This course presents an integrated approach to the study of protein function. Topics include proteomic techniques in protein profiling, mass spectrometry, 2-D gel electrophoresis, yeast 2-hybrid analysis, protein chips, protein purification, imaging, surface plasmon resonance, calorimetry, bioinformatics and protein evolution, protein modifications and processing, interpretation and applications of 3-D structure, protein structure-function relationships. Three lecture hours per week; Offered jointly with BCHM-410* with additional work required. PREREQUISITES: BCHM-310 or 315*/316*/317* or permission of the instructor. EXCLUSION:
BCHM-410*

BMED-811* Advanced Molecular Biology (3CU)
This course concentrates on the molecular biology of mammalian models particularly mechanisms involved in human diseases. The human genome project, forensic analysis, DNA diagnostics of human diseases, models of transcriptional and growth regulation and cancer, DNA repair, RNA processing and translation are all discussed. Emphasis on recent findings and course materials will be drawn from current reviews. Three lecture hours per week. Winter. Offered jointly with
BCHM-411* with additional work required. PREREQUISITE: BCHM-310 or 315*/316*/317* or permission of the instructor EXCLUSION: BCHM-411*.

BMED-813* Advances in Neuropharmacology (3CU)
Recent advances in understanding neurotransmission and pharmacology in the central nervous system will be discussed. The current literature describing progress in understanding molecular, cellular and behavioural aspects of brain function, and the impact of drugs and disease, will be examined. Winter; seminars and tutorials. Given in years ending with an uneven number.

BMED-815* Mechanistic Toxicology (3CU)
An advanced, problem-based course focusing on current approaches to the study of mechanisms of chemical toxicity. Winter; 3 hour seminars and tutorials. Given in years ending with an even number. PREREQUISITE: PHAR-416* or equivalent.

BMED-854* Cardiovascular Sciences (3CU)
An advanced inter-disciplinary course studying the anatomy, pharmacology and physiology of the cardiovascular system at the molecular and cellular level. The course is comprised of lectures, discussion and student seminars based on recent literature. Winter term, 3 hour seminar.

Opportunities and Career Paths for Grads

Opportunities

Queen’s offers its students a perfect balance of engagement with rigorous academic programs and access to first class practitioners and learning facilities.  Both the diploma and M.A. programs are cross-disciplinary -- taught by a combination of instructors from the School of Computing and the Faculty of Health Sciences.

Career paths – employment opportunities

  • Chief Information Officers (CIOs)
  • Chief Medical Information Officers (CMIOs)
  • Chief Medical Officers (CMOs)
  • Chief Nursing Information Officers (CNIOs)
  • Biomedical and clinical research, including the application of genomics and molecular biology
  • Clinical Informaticist
  • Consumer health and Public health
  • Imaging
  • Directors of Medical Informatics
  • Project managers & designers
  • Researchers
  • Programmers  & analysts
  • Health information technology (HIT) educators, trainers, consultants
  • Medical / technical writers
  • Nursing informatics specialists
  • Account representatives

The following examples of the workplace environments for our graduates:

  • Academic institutions
  • Community health centers
  • Consultanting agencies
  • eHealth companiesHospitals and health systems
  • Physician practices and clinics
  • Health care agencies within federal and state government
  • Health information technology system vendors
  • Health insurance companies
  • Pharmaceutical companies

Our City - Kingston Ontario Canada

We're proud to say that not only are we an official "Intelligent Community" but that the BBC named Kingston as one of the greatest university towns in the world. Kingston is a home-away-from-home not only for students from Queen’s, but also for those attending the Royal Military College and St. Lawrence College - nearly 30,000 in all! We are a student town. We are in the middle of everything - Montreal, Toronto, Ottawa and even New York - all less than a day trip away. Instagram also ranked us the happiest city on the planet. So why not learn alongside the smartest, happiest people around?

Learn more about Kingston

Application Process

To be considered for admission to the Graduate Diploma or the MBI, an applicant must hold a minimum of a BSc (Honours) degree in biology, life sciences, biochemistry, medical sciences, computer science, biostatistics, engineering, and related disciplines, who are interested in designing and implementing quantitative and computational methods that solve challenging problems across the entire spectrum of biology and medicine, and who wish to develop the skills required for a range of exciting careers in medicine, research and development, or industry. The minimum acceptable average for admissions to these programs is B+ in the third and fourth years of the student’s undergraduate program (all courses considered). Students applying from outside of North America whose native language is not English are required to submit TOEFL scores. Although the program is aimed at recent graduates from undergraduate programs, applicants from professional programs such as medicine and nursing are also welcome.

Important Dates & Deadlines
Offer of Admissions to begin: February 1, 2018
Deadline to Apply (for both programs): April 1, 2018
Final Decisions will be Communicated: April 1, 2018

How-to Apply