Articles

Systems Biology

What is Systems Biology?

The field of systems biology is relatively new, only coming to the fore with the advent of technological and computational advances that permit the collection and analysis of large datasets. Unlike the reductionist approach of the past century and a half that attempts to understand a system by understanding its individual constituent parts in isolation, systems biology attempts to understand the system by understanding the interactions between constituent parts. In the study of systems biology, the system itself is the thing to be studied. As a consequence, it is necessary to make trade-offs by approximating the behavior of each constituent of that system. A system is defined by the constituent parts that comprise its key behaviors. As a result, a system can be a collection of molecules, a single cell, a tissue, an organ, or a body. For each system, the constituent parts are most often considered to be the next step down in scale. For example, if the body is defined as the system, the most logical constituent parts would be organs. If the organ is the system, the cells and tissues that comprise the organ are the constituent parts. The behavior of biological systems is dictated by nonlinearities that result in outcomes that are emergent from the interactions between the constituent parts. It is therefore essential in the study of systems biology that the researchers remain sensitive to the idea that small changes in one part or another can potentially lead to large changes in the behavior of the system. It is for these reasons that computational models are an indispensable tool in the study of biological systems.

 

Why model?

Computational modeling provides the means to simulate a complex system and examine its behavior. There are several reasons to model, including gaps in experimental data, high cost of biological experiments, and nonlinearities that make predicting the behavior of a system rather challenging.

 

What is the purpose of this course?

The purpose of the course is to introduce students to the basic tenants of modeling biological systems and understanding biological phenomena as emergent properties of systems. This course will take students through a defined approach to generating models of biological systems, initially in order to provide structure for taming the complexity of biological systems. However, it is undeniable that there is also an art to modeling. As students progress through the course and work through their own original research via the project portion of the course, they will be guided into making judgement calls and applying the art of modeling. It is hopeful that the project work will contribute to a body of knowledge that pushes the fields of both systems biology and chemical engineering in such a way as to be published in peer-reviewed journals.

 

Who is this course designed for?

The course is primarily designed for chemical engineers, mathematicians, and others with a strong quantitative background. An understanding of calculus, differential equations, and computer programming are all very desirable and lead to a high probability of success in the course. Even though background knowledge in biological and medical sciences can be helpful, it is not a prerequisite for success in this course. Much of the needed biology can be acquired along the way during the project component of the course. While deep understanding in a field or discipline is often the ultimate goal of university training, it is the bridge-builders and those who can think simultaneously like an engineer and like a biologist who will drive future innovations.

 

Course structure

The course structure is intended to have a certain amount of flexibility depending upon the local needs of the students and faculty. There are core lectures whose information is important to success on the projects and to building toward a general understanding of systems biology, human physiology, and modeling. A recommended order is presented for the core lectures in so much that some build upon previously introduced topics, however, each could stand alone depending upon the prior knowledge and understanding of the individual student. The Extended Topics include several lectures that are meant to enrich the course for all students or to serve the specific needs to only select students, depending upon the nature of their project or purely academic interests. The Extended Topics are not presented in any order and may considered in any order, interspersed with the Core Topics, or ignored entirely.

 

While the lecture and homework components of the course are valuable, the greatest learning often comes from actually doing the work. Therefore, the project component of the course is incredibly important. Any one project will not encompass all of the tools or topics presented in the core lectures, but will permit students to consider specific ideas much more deeply. Even well-defined projects will have a certain amount of ambiguity and difficulty, which is why as essential component of the course is the project mentors. Through working closely with one or more mentors, students will learn how to overcome obstacles and deal with novel challenges that necessarily come up in the modeling process.

 

Core Topics

  1. What is Systems Biology?
    1. What do we mean by “system”?
    2. How does systems biology differ from a reductionist approach?
    3. What are the strengths of a systems approach?
  2. Why do we model?
    1. What are the objectives of modeling?
    2. What can modeling accomplish that cannot be accomplished in other ways?
  3. How do we generate models?
    1. What are the steps of modeling?
    2. What does this process look like when applied?
  4. What are the different types of systems biology models?
    1. What is a rules-based model?
    2. What is an ordinary differential equation (ODE) model?
    3. What is a process control model?
    4. What software packages exist to aid in these modeling efforts?
  5. How can we think of the human body in terms of engineering principles?
    1. How is the human body organized?
    2. What are the major organ systems?
      1. What does each organ system do?
      2. How do organ systems communicate with each other (blood, lymph, neuronal)?
    3. What are some ways to approximate human physiology using engineering ideas?
  6. How can we use Netlogo to make rules-based models?
    1. What are the components of a Netlogo model?
    2. How are the rules dictated; what syntax is used?
    3. What are some examples of models that have been generated with Netlogo?
    4. How can I turn biological knowledge into a Netlogo rule?
  7. How can we use Matlab to make an ODE model?
    1. What are some examples of reactions that can be modeled by ODE’s?
    2. What do these reactions look like when coded in Matlab?
    3. What can I use to solve a system of ODE’s simultaneously?
    4. How can I generate a meaningful representation of my results?
  8. How can I use Simulink to make a process control model?
    1. How can represent the structure of my model in Simulink?
    2. What transfer functions describe biological processes?
  9. What is a connectivity map and how can I create one?
    1. What does a connectivity map represent?
    2. How can I turn information from biological literature into a connectivity map?
    3. How and when should I use software tools, like Cytoscape, to make a representation of my connectivity map?
  10. What is a physiologically-based pharmaco-kinetic (PBPK) model?
    1. What is the goal of a PBPK model?
    2. What are some common assumptions of PBPK models?
    3. What are the steps needed to generate a PBPK model?
    4. What are some examples of PBPK models?
  11. How can I validate my model or perform a reality check?
    1. How can I compare my model with experimental data?
    2. How can I tune my model?
    3. What is a sensitivity analysis?
    4. What do I do if there is no experimental data to validate the model against?

 

Extended Topics

  1. What is “big data” and how does it drive systems biology?
    1. What are the different types of “-omics” datasets and how are they collected?
    2. What are the shortcomings of different types of -omics data?
    3. How is -omics data used in systems biology generally?
  2. How is the human nervous system organized?
    1. What does the nervous system do in different parts of the body?
    2. How is information passed along neurons and between neurons?
    3. Should I include parts of the nervous system in my model?
  3. How does the brain process information?
    1. How is the brain organized?
    2. How is information transmitted and stored in the brain?
    3. How does the biology occurring in the body affect the brain?
    4. How does the brain affect the biology occurring in the rest of the body?
    5. Should I include individual aspects of the brain in my model?
  4. What is the role of the immune system and how does it interact with the rest of the body?
    1. What are the main constituent cell types in the immune system?
    2. How does the immune system respond to sickness or injury?
    3. How does the immune response affect different organ systems?
    4. Should I include parts of the immune system in my model?
  5. How does the body keep certain compartments separate through barrier systems?
    1. What are the main barrier systems in the body?
      1. Gut permeability barrier
      2. Blood-brain barrier
      3. Blood-testis barrier
      4. Placenta-fetus barrier
    2. What does each barrier let in and keep out?
    3. What mechanisms are used to generate these barrier systems?
  6. How are enzyme kinetics represented mathematically and how can I model them?
    1. How do enzymes catalyze reactions?
    2. What kind of mathematical equations can be used to represent enzymatic reactions?
    3. What is the difference between zero-order, first order, and second order reactions?
    4. Should I integrate enzyme kinetics into my model and how might I do it?

 

Project Guidelines

The project component of this course is absolutely essential to the learning and should be given top priority. A series of project ideas will be available from the course designers, but you are encouraged to consider projects that are within your own domain or area of interest. It is helpful to work in groups of 2-3 individuals in order to get good interaction, discussion, and division of labor. Many of the projects will not a have a scope that requires more than 3 individuals, so it is highly recommended to limit group size accordingly. In order for the projects to be successful, it is important to have one or more project mentors whose role it is to coach and guide the students. It may be necessary to have more than one mentor, since it is rare to find a single mentor that will have the required biological, mathematical, and practical modeling knowledge all at the same time. One of the strengths of the project is the necessary multi-disciplinary approach that must be taken in order to be successful. This is the way future academic and industrial research will find its path forward and it crucial to give students the experience in working in such an environment.

 

Each project should have a clearly stated goal, perhaps with intermediate goals that build up to an overall goal. This goal may fluctuate as more information is gathered and the project progresses. That is okay, so long as at any given point, there is a clear goal.

 

The first step to any project is to gain background knowledge. This is different from a literature search, which will be addressed next. Background knowledge is often textbook level information about a topic that does not require digging through scientific publications (although review articles may be helpful). Especially with regard to biological information, many engineering students will not have the background knowledge to jump right into the current literature.

 

A literature review is also essential and has two main parts. The first is an examination of the modeling literature for work that is closely related or in some other way similar to the modeling work that is to be done in the project. The second is an examination of the biological literature that will help provide recent context and relevance to the modeling project. This latter review can be challenging and it will be helpful for mentors to keep in touch especially at this point. It will be essential to keep track of the literature review with a source/citation manager. We recommend Mendeley given its user-friendly interface, ability to share resources virtually, and its open-source, cost free nature. There are countless other programs that will also work just as well, so use whatever is comfortable.

 

How group members and mentors organize their time is left open, however, we highly recommend regular weekly meetings at a bare minimum in order to report progress, share difficulties, and maintain momentum.

 

While the primary goal of the project component is to practice and hone the skills required in making models of biological systems, a secondary goal is publication. Publications, however great or small, are the mean by which scientists put their work out into the community for scrutiny and to enhance the field bit by bit. Every project should be aimed as a publication eventually, even if it requires many different groups of students over the course of years to accomplish. As a consequence, any project work should be well-documented such that even if a publication is not within reach by the end of the course, the work done provides a foundation for a future group to take it one step closer to publication. Contribution to the scientific literature is the ultimate goal of an academic scientist and this is an important mindset to instill in students of any discipline.

Industrial Chemical Technology

This is a truly unique course taught by Dr. Jeffrey Siirola, a leader and pioneer in chemical engineering. The course was first offered at Carnegie Mellon University in 2011 while Dr. Siirola was
the Distinguished Professor in Energy Systems. He is currently Professor of Engineering Practice at Purdue University

The course, which was primarily aimed at junior students of Chemical Engineering and Public Policy, was extremely well received as it provides a comprehensive view on the evolution of the chemical industry, emphasizing major technology changes and sustainability issues.

Course description:

This course surveys key sectors of the chemical processing industries and discusses the structure of the industry and the historical development and evolution of the technologies which have shaped them and the common flowsheet elements which have proven to be commercially successful. Examples are drawn from a range of industry sectors, production scales, chemistries, and enabling technologies. The industry is examined in light of factors which have most influenced its development including raw materials of choice, energy availability, and the development of new unit operations, as well as those which will influence its future course including advances in science and technology, environmental impact minimization, water availability, and sustainability concerns.

Systems Biology Old

What is Systems Biology?

The field of systems biology is relatively new, only coming to the fore with the advent of technological and computational advances that permit the collection and analysis of large datasets. Unlike the reductionist approach of the past century and a half that attempts to understand a system by understanding its individual constituent parts in isolation, systems biology attempts to understand the system by understanding the interactions between constituent parts. In the study of systems biology, the system itself is the thing to be studied. As a consequence, it is necessary to make trade-offs by approximating the behavior of each constituent of that system. A system is defined by the constituent parts that comprise its key behaviors. As a result, a system can be a collection of molecules, a single cell, a tissue, an organ, or a body. For each system, the constituent parts are most often considered to be the next step down in scale. For example, if the body is defined as the system, the most logical constituent parts would be organs. If the organ is the system, the cells and tissues that comprise the organ are the constituent parts. The behavior of biological systems is dictated by nonlinearities that result in outcomes that are emergent from the interactions between the constituent parts. It is therefore essential in the study of systems biology that the researchers remain sensitive to the idea that small changes in one part or another can potentially lead to large changes in the behavior of the system. It is for these reasons that computational models are an indispensable tool in the study of biological systems.

 

Why model?

Computational modeling provides the means to simulate a complex system and examine its behavior. There are several reasons to model, including gaps in experimental data, high cost of biological experiments, and nonlinearities that make predicting the behavior of a system rather challenging.

 

What is the purpose of this course?

The purpose of the course is to introduce students to the basic tenants of modeling biological systems and understanding biological phenomena as emergent properties of systems. This course will take students through a defined approach to generating models of biological systems, initially in order to provide structure for taming the complexity of biological systems. However, it is undeniable that there is also an art to modeling. As students progress through the course and work through their own original research via the project portion of the course, they will be guided into making judgement calls and applying the art of modeling. It is hopeful that the project work will contribute to a body of knowledge that pushes the fields of both systems biology and chemical engineering in such a way as to be published in peer-reviewed journals.

 

Who is this course designed for?

The course is primarily designed for chemical engineers, mathematicians, and others with a strong quantitative background. An understanding of calculus, differential equations, and computer programming are all very desirable and lead to a high probability of success in the course. Even though background knowledge in biological and medical sciences can be helpful, it is not a prerequisite for success in this course. Much of the needed biology can be acquired along the way during the project component of the course. While deep understanding in a field or discipline is often the ultimate goal of university training, it is the bridge-builders and those who can think simultaneously like an engineer and like a biologist who will drive future innovations.

 

Course structure

The course structure is intended to have a certain amount of flexibility depending upon the local needs of the students and faculty. There are core lectures whose information is important to success on the projects and to building toward a general understanding of systems biology, human physiology, and modeling. A recommended order is presented for the core lectures in so much that some build upon previously introduced topics, however, each could stand alone depending upon the prior knowledge and understanding of the individual student. The Extended Topics include several lectures that are meant to enrich the course for all students or to serve the specific needs to only select students, depending upon the nature of their project or purely academic interests. The Extended Topics are not presented in any order and may considered in any order, interspersed with the Core Topics, or ignored entirely.

 

While the lecture and homework components of the course are valuable, the greatest learning often comes from actually doing the work. Therefore, the project component of the course is incredibly important. Any one project will not encompass all of the tools or topics presented in the core lectures, but will permit students to consider specific ideas much more deeply. Even well-defined projects will have a certain amount of ambiguity and difficulty, which is why as essential component of the course is the project mentors. Through working closely with one or more mentors, students will learn how to overcome obstacles and deal with novel challenges that necessarily come up in the modeling process.

 

How to use this Learning Management system

  • You will see a list of courses you have ordered/opted for .
  • Please pick up one course to start.
  • The course is divided in LESSONS and then TOPICS.
  • You will see the list of lessons at the right column of the page.
  • Click on the Lesson and it will open the TOPICS menu below it.
  • You can read the LESSON and then Start on the first TOPIC and go forward.
  • Once you complete on TOPIC or a LESSON please click on MARK COMPLETE to record the completion of that segment.
  • Marking the completion is required to let you go forward in the course and finally get the certificate.
  • There will be QUZIZZES in some courses either after each LESSON or at the end of the COURSE. Please complete it.
  • In the end please call us at 416-724-5940 or send us an email at support@sunjog.com to let us know that you have completed the course.

HAPPY LEARNING

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