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Introduction to Systems Biology

Ravi Iyengar, PhD

This course will introduce the student to contemporary Systems Biology focused on mammalian cells, their constituents and their functions. Biology is moving from molecular to modular. As our knowledge of our genome and gene expression deepens and we develop lists of molecules (proteins, lipids, ions) involved in cellular processes, we need to understand how these molecules interact with each other to form modules that act as discrete functional systems. These systems underlie core subcellular processes such as signal transduction, transcription, motility and electrical excitability. In turn these processes come together to exhibit cellular behaviors such as secretion, proliferation and action potentials. What are the properties of such subcellular and cellular systems? What are the mechanisms by which emergent behaviors of systems arise? What types of experiments inform systems-level thinking? Why do we need computation and simulations to understand these systems?

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This course will introduce the student to contemporary Systems Biology focused on mammalian cells, their constituents and their functions. Biology is moving from molecular to modular. As our knowledge of our genome and gene expression deepens and we develop lists of molecules (proteins, lipids, ions) involved in cellular processes, we need to understand how these molecules interact with each other to form modules that act as discrete functional systems. These systems underlie core subcellular processes such as signal transduction, transcription, motility and electrical excitability. In turn these processes come together to exhibit cellular behaviors such as secretion, proliferation and action potentials. What are the properties of such subcellular and cellular systems? What are the mechanisms by which emergent behaviors of systems arise? What types of experiments inform systems-level thinking? Why do we need computation and simulations to understand these systems?

The course will develop multiple lines of reasoning to answer the questions listed above. Two major reasoning threads are: the design, execution and interpretation of multivariable experiments that produce large data sets; quantitative reasoning, models and simulations. Examples will be discussed to demonstrate “how” cell- level functions arise and “why” mechanistic knowledge allows us to predict cellular behaviors leading to disease states and drug responses.

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What's inside

Syllabus

Systems Level Reasoning | Molecules to Pathways
Module description goes here.
Pathways to Networks | Physical Forces and Electrical Activity in Cell Biology
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Mathematical Representations of Cell Biological Systems | Simulations of Cell Biological Systems
Experimental Technologies | Network Building and Analysis
Midterm
Analysis of Networks | Topology to Function
Strengths and Limitations of Different Types of Models | Identifying Emergent Properties
Emergent Properties: Ultrasensitivity and Robustness | Case Studies
Case Studies | Systems Biomedicine | Systems Pharmacology and Therapeutics | Perspective
Final

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Develops understanding of contemporary Systems Biology and how it is moving from molecular to modular perspectives in order to understand cellular functions and processes
Provides a strong foundation for understanding how cellular-level functions arise and how mechanistic knowledge allows us to predict cellular behaviors
Examines the strengths and limitations of different types of mathematical representation models in understanding emergent cellular systems properties

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Reviews summary

Systems biology introductory overview

Learners say that this course offers a broad overview of the key concepts in Systems Biology. Although this is a well-received course by learners, it has its drawbacks. Those new to systems biology or biology in general may find it difficult to follow given the complex topics covered. The fast-paced environment assumes prior knowledge. Despite its engaging assignments and informative lectures, the course could be more clear and coherent. However, there are learners who found the course organized and helpful in furthering their knowledge.
Engaging assignments.
"Personally, I appreciate the very well thought out curriculum and I find the assignments helpful. I enjoy it so far."
No instructor participation in the forums.
"No mentor intervention in the forums. Ever."
Content is not well-organized.
"it was done in a very poorly way."
"It is more like a series of informal seminars given to peers, who needs refreshing a specific topic."
Assumes prior knowledge in Biology.
"Having completed somewhere in the region of 70 online courses I can say with complete honesty that "Introduction to Systems Biology" is the worst online course."
"This, despite passing the quizzes. I really fail to see which audience the course is supposed to target."
Has a lot of jargon and unfamiliar terms.
"There are problems with the target audience of the course."
"The presentation of the topics is rather messy and it seems to be assumed that you are familiar with the jargon and technicalities of molecular biology and mathematics."

Career center

Learners who complete Introduction to Systems Biology will develop knowledge and skills that may be useful to these careers:
Computational Biologist
Computational Biologists use computer science and mathematics to solve biological problems. They develop algorithms and software to analyze biological data and to model biological systems. This course can help you build a foundation in computer science and mathematics, which are essential skills for Computational Biologists. You will also learn about experimental design and data analysis, which are important skills for anyone working with data.
Biostatistician
Biostatisticians collect and analyze data to develop mathematical models that describe biological systems. They use these models to understand the causes and effects of various biological phenomena. This course can help you build a foundation in quantitative reasoning and modeling, which are essential skills for Biostatisticians. You will also learn about experimental design and data analysis, which are important skills for anyone working with data.
Data Scientist
Data Scientists use data to solve problems. They collect, analyze, and interpret data to identify trends and patterns. This course can help you build a foundation in data science, which is a valuable skill in a variety of fields. You will also learn about experimental design and data analysis, which are important skills for anyone working with data.
Operations Research Analyst
Operations Research Analysts use mathematical models to solve problems in a variety of industries, such as manufacturing, transportation, and healthcare. This course can help you build a foundation in operations research, which is a valuable skill in a variety of fields. You will also learn about experimental design and data analysis, which are important skills for anyone working with data.
Quantitative Analyst
Quantitative Analysts use mathematical models to analyze financial data. They use these models to make investment decisions and to manage risk. This course can help you build a foundation in quantitative analysis, which is a valuable skill in the financial industry. You will also learn about experimental design and data analysis, which are important skills for anyone working with data.
Research Scientist
Research Scientists conduct research in a variety of fields, such as biology, chemistry, and physics. They use a variety of methods to investigate scientific questions, including experimentation, modeling, and data analysis. This course can help you build a foundation in research methods, which are essential for Research Scientists. You will also learn about experimental design and data analysis, which are important skills for anyone working with data.
Machine Learning Engineer
Machine Learning Engineers develop and implement machine learning models. They use these models to solve problems such as image recognition, natural language processing, and fraud detection. This course can help you build a foundation in machine learning, which is a valuable skill in a variety of fields. You will also learn about experimental design and data analysis, which are important skills for anyone working with data.
Electrical Engineer
Electrical Engineers design, develop, and implement electrical systems. They use a variety of engineering disciplines to create systems that generate, transmit, and distribute electricity.
Systems Engineer
Systems Engineers design, develop, and implement systems. They use a variety of engineering disciplines to create systems that meet the needs of users. This course can help you build a foundation in systems engineering, which is a valuable skill in a variety of industries. You will also learn about experimental design and data analysis, which are important skills for anyone working with data.
Software Engineer
Software Engineers design, develop, and implement software applications. They use a variety of programming languages and technologies to create software that meets the needs of users. This course can help you build a foundation in software engineering, which is a valuable skill in a variety of industries. You will also learn about experimental design and data analysis, which are important skills for anyone working with data.
Mechanical Engineer
Mechanical Engineers design, develop, and implement mechanical systems. They use a variety of engineering disciplines to create systems that convert energy into motion.
Chemical Engineer
Chemical Engineers design, develop, and implement chemical processes. They use a variety of engineering disciplines to create processes that produce chemicals and other products. This course can help you build a foundation in chemical engineering, which is a valuable skill in the chemical industry. You will also learn about experimental design and data analysis, which are important skills for anyone working with data.
Biomedical Engineer
Biomedical Engineers design, develop, and implement medical devices and technologies. They use a variety of engineering disciplines to create devices and technologies that improve patient care. This course can help you build a foundation in biomedical engineering, which is a valuable skill in the medical industry. You will also learn about experimental design and data analysis, which are important skills for anyone working with data.
Civil Engineer
Civil Engineers design, develop, and implement civil infrastructure. They use a variety of engineering disciplines to create structures and systems that meet the needs of society.
Nuclear Engineer
Nuclear Engineers design, develop, and implement nuclear systems. They use a variety of engineering disciplines to create systems that generate nuclear power.

Reading list

We've selected nine books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Introduction to Systems Biology.
Provides a comprehensive overview of systems biology, covering topics such as molecular networks, dynamical modeling, and data analysis.
Provides a comprehensive overview of biochemistry, covering topics such as metabolism, enzyme kinetics, and protein structure.
Provides an introduction to mathematical modeling in systems biology, covering topics such as ordinary differential equations, partial differential equations, and stochastic models.
Provides a comprehensive overview of systems biology, covering topics such as molecular networks, dynamical modeling, and data analysis.

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