Summer Course
Systems Biology of Disease
June 19 - 23, 2017
Offered by the Institute for Systems Biology and the Center for Systems Biology
Hosted by
Institute for Systems Biology and Center for Systems Biology
Course Abstract
Systems Biology Of Disease
Systems Biology is a holistic approach to deciphering complexity and emergent properties of biological systems. Embracing systems-biology practices helps us to reveal molecular and cellular networks that relay information and ultimately, design predictive, multi-scale models for spatiotemporal patterns of biological systems. During this process, systems biology drives innovation through iterative biology-driven advancements in technology and computation. One of the current challenges in the field is how we phrase questions and design studies that will help us to understand the complexity in “larger” systems, including organisms of greater medical relevance, such as mice and humans.

This course aims to disseminate systems approaches and analysis tools to study human biology in health and disease. This course will also introduce systems biomedicine, which is the application of a systems view to disease. We will demonstrate the state of the art of systems biology for medical applications (i.e. how to stratify diseases, and identify biomarkers and drug targets) and discuss key opportunities and challenges for the application of systems biology approaches to medicine. This course is designed as an introduction to systems biomedicine with lectures, hands on interactive sessions, and panel discussions. As such, it is aimed at graduate students, post-doctoral fellows and principal investigators with an interest in systems biomedicine.

Upon completing this course, trainees will have learned: 1) core concepts of systems biology, 2) applications to systems biomedicine, 3) how to construct classifiers that stratify diseases, 4) how to discover biomarkers, and 5) how to discover drug targets. The final day will provide trainees with an opportunity to apply what they have learned to analyze real data resulting from an ongoing Tuberculosis study at Center for Infectious Disease Research.
Expert Speaker Series 2017
More Speakers Coming Soon
Daniel Zak, PhD
Principal Scientist, Center for Infectious Disease Research
David Sherman, PhD
Professor, Center for Infectious Disease Research
Dave S. Hoon, MS, PhD
Director, Translational Molecular Medicine, John Wayne Cancer Institute, Providence Saint John's Health Center
Bernard A. Fox, PhD
Chief, Laboratory of Molecular and Tumor Immunology, Robert W. Franz Cancer Research Center in the Earle A. Chiles Research Institute at Providence Cancer Center
Associate Professor, MMI and Env and Biomolec systems Leader, Tumor Immunology Focus Group, OHSU Cancer Institute
Michael C. Jensen, MD
Jan & Jim Sinegal Endowed Chair, Childhood Cancer Research Professor, Division of Pediatric Hematology-Oncology, UWSOM Joint Member, Clinical Research Division, FHCRC
Director, Ben Towne Center for Childhood Cancer Research, SCRI
Adjunct Professor, UW Department of Bioengineering
ISB Speakers
Lee Hood, MD, PhD
Professor & President, Institute for Systems Biology
John Aitchison, PhD
Professor, Institute for Systems Biology
Nitin Baliga, PhD
Professor, SVP & Director, Institute for Systems Biology
Sui Huang, MD, PhD
Professor, Institute for Systems Biology
Rob Moritz, PhD
Professor, Institute for Systems Biology
Nathan Price, PhD
Professor & Associate Director, Institute for Systems Biology
Ilya Shmulevich, PhD
Professor, Institute for Systems Biology
Jeff Ranish, PhD
Associate Professor, Institute for Systems Biology
Naeha Subramanian, PhD
Assistant Professor, Institute for Systems Biology

General Daily Structure

In the sections below you will find an overview for each day.
Day One
Systems Biomedicine
Systems biomedicine is the application of systems biology approaches to develop multi-scale models that provide better classification, biomarkers and drug targets for human disease. For the first day of the course the concepts of systems thinking, networks, and systems properties will be described with examples. Additionally trainees will learn basic skills with R, get a crash course in systems biomedicine experimental design and organize into teams of individuals with complementary skills to tackle the experimental design for a systems biomedicine approach to cancer.
Day Two
Patient Stratification
Human diseases while appearing to be homogeneous pathologically, clinical phenotypes can in actuality by very heterogeneous in cause. Pathologists have known for quite some time this was the case because patients with seemingly homogeneous pathology could result in very different patient outcomes. The ability to produce systems level molecular profiles from diseased patient’s tissue has provided a means to stratify patients based upon molecular signatures. This patient stratification into subgroups with molecular signatures is a vital step that is required to focus studies of the efficacy of biomarkers and drug targets to only those individuals where they will have an effect. Patient stratification can also be applied to patients that have similar etiologies and disease processes, to characterize their various stages of disease. These cross-sectional datasets are especially important for monitoring patients during treatment to determine drug efficacies.
Day Three
Discovering Biomarkers
In the context of this course a biomarker is considered a quantifiable molecular phenotype that can be measured and evaluated as an indicator of a biological systems state, pathogenic process or as a means to assess the therapeutic efficacy of a drug. Patient stratification into actionable subgroups is a very important first step before identifying biomarkers. Typically the features that make up the molecular signatures used to stratify patients into these actionable subgroups are viable candidates for biomarkers. The development of biomarkers is a multi-step process involving discovering viable biomarkers, developing methods to screen them in non-invasive ways (blood or urine), and assessing their clinical implications.
Day Four
Discovering Drug Targets
Improving the standard of care for persons with a disease is the end goal of systems biomedicine. The discovery of drug targets can be accomplished in a variety of ways but one underlying theme is the integration of prior information about the disease etiology. Typically discovering drug targets relies heavily upon both patient stratification into actionable subgroups and biomarkers. Stratifying patients into actionable subgroups is the first step in the process as it defines homogeneous sets of patients that are likely to respond similarly to therapeutic interventions. Discovering biomarkers provides the means for early detection and non-invasive subtyping that allow persons developing or with established disease to be identified and given the appropriate therapeutic intervention. Biomarkers are also vital to monitor the efficacy of therapeutically intervention for discovered drug targets. Together with the successful idsentification of actionable patient subgroups and biomarkers to discern them in the clinic, it will be possible to develop therapies, which improve patient outcome and reduce the complications associated with invasive procedures or undesirable off-target effects.
Day Five
Example Applications of Systems Biology
During the morning mini-symposium will be held to show trainees the many ways in which systems biology can be applied to biomedical studies. A lunch will be provided where trainees can discuss with the ISB faculty what they have learned and questions they may have about applying systems biology to biomedical studies. Following the faculty lunch, Dr. Lee Hood will address the students with his vision of how the healthcare system must be transformed. At the end of Dr. Hood’s lecture will be a discussion of all that was presented in the course and trainees will be asked to discuss how these concepts can be applied to their own research.

Preparatory Prerequisites
Before attending the course we strongly recommend that trainees take the ‘R Programming’ course from coursera.org. You will need to make an account with courser (which is free), and then take the courser on ‘R Programming’ which takes a 4 weeks and is suggested to take 7-9 hours of time per week. Completion of this course is not required, but is highly recommended for those who are not familiar with R. Interested trainees may also take the edX course ‘Statistics and R for the Life Sciences’ to supplement their R skills.
Course Equipment
To participate in this course each trainee will want to have a computer of their own. We will provide a list of software that the trainee is to have installed on their computer before coming to the course. A sample snippet of code will be used to determine if they have successfully installed the applications. If they don’t have them installed properly they can communicate the issues to us and we will help the as necessary. The goal being that they will come with computers ready to be used for the data analysis and exploration sections we have devised. We will also provide our old course laptops for those who do not have a laptop of their own or for those who have issues we cannot fix. These will be pre-installed with working versions of all software.
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