This course is part of the Systems Biology and Biotechnology Specialization
Network Analysis in Systems Biology
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About this Course
4.5
103 ratings
An introduction to data integration and statistical methods used in contemporary Systems Biology, Bioinformatics and Systems Pharmacology research. The course covers methods to process raw data from genome-wide mRNA expression studies (microarrays and RNA-seq) including data normalization, differential expression, clustering, enrichment analysis and network construction. The course contains practical tutorials for using tools and setting up pipelines, but it also covers the mathematics behind the methods applied within the tools. The course is mostly appropriate for beginning graduate students and advanced undergraduates majoring in fields such as biology, math, physics, chemistry, computer science, biomedical and electrical engineering. The course should be useful for researchers who encounter large datasets in their own research. The course presents software tools developed by the Ma’ayan Laboratory (http://labs.icahn.mssm.edu/maayanlab/) from the Icahn School of Medicine at Mount Sinai, but also other freely available data analysis and visualization tools. The ultimate aim of the course is to enable participants to utilize the methods presented in this course for analyzing their own data for their own projects. For those participants that do not work in the field, the course introduces the current research challenges faced in the field of computational systems biology.
Syllabus - What you will learn from this course
Week
1Course Overview and Introductions
The 'Introduction to Complex Systems' module discusses complex systems and leads to the idea that a cell can be considered a complex system or a complex agent living in a complex environment just like us. The 'Introduction to Biology for Engineers' module provides an introduction to some central topics in cell and molecular biology for those who do not have the background in the field. This is not a comprehensive coverage of cell and molecular biology. The goal is to provide an entry point to motivate those who are interested in this field, coming from other disciplines, to begin studying biology.
3 videos (Total 52 min), 4 readings, 3 quizzes
3 videos
Introduction to Cell Biology16m
Introduction to Molecular Biology19m
4 readings
Course Logistics10m
Grading Policy10m
Resources and Links to Additional Materials10m
MATLAB License10m
3 practice exercises
Introduction to Complex Systems20m
Introduction to Cell Biology18m
Introduction to Molecular Biology20m
Week
2Topological and Network Evolution Models
In the 'Topological and Network Evolution Models' module, we provide several lectures about a historical perspective of network analysis in systems biology. The focus is on in-silico network evolution models. These are simple computational models that, based of few rules, can create networks that have a similar topology to the molecular networks observed in biological systems.
4 videos (Total 45 min), 4 quizzes
4 videos
Duplication-Divergence and Network Motifs8m
Large Size Motifs and Complex Models of Network Evolution10m
Network Properties of Biological Networks11m
4 practice exercises
Rich-Get-Richer14m
Duplication-Divergence and Network Motifs16m
Large Size Motifs16m
Topological Properties of Biological Networks18m
Week
3Types of Biological Networks
The 'Types of Biological Networks' module is about the various types of networks that are typically constructed and analyzed in systems biology and systems pharmacology. This lecture ends with the idea of functional association networks (FANs). Following this lecture are lectures that discuss how to construct FANs and how to use these networks for analyzing gene lists.
4 videos (Total 58 min), 4 quizzes
4 videos
Genes2Networks and Network Visualization16m
Sets2Networks - Creating Functional Association Networks14m
Genes2FANs - Analyzing Gene Lists with Functional Association Networks14m
4 practice exercises
Types of Biological Networks16m
Genes2Networks and Network Visualization14m
Functional Association Networks with Sets2Networks16m
Functional Association Networks with Genes2FANs16m
Week
4Data Processing and Identifying Differentially Expressed Genes
This set of lectures in the 'Data Processing and Identifying Differentially Expressed Genes' module first discusses data normalization methods, and then several lectures are devoted to explaining the problem of identifying differentially expressed genes with the focus on understanding the inner workings of a new method developed by the Ma'ayan Laboratory called the Characteristic Direction.
5 videos (Total 41 min), 2 quizzes
5 videos
Characteristic Direction Method - Part 18m
Characteristic Direction Method - Part 27m
Characteristic Direction Method - Part 310m
Characteristic Direction Method - Part 45m
2 practice exercises
Data Normalization14m
Characteristic Direction12m
4.5
Top Reviews
By FP•Jun 3rd 2016
Excellent course to get deep into the data analysis of system biology experimentation.
By CC•Apr 6th 2016
Its really a very interesting course ,and very informative
Instructor
Avi Ma’ayan, PhD
Director, Mount Sinai Center for BioinformaticsProfessor, Department of Pharmacological Sciences
About Icahn School of Medicine at Mount Sinai
The Icahn School of Medicine at Mount Sinai, in New York City is a leader in medical and scientific training and education, biomedical research and patient care.
About the Systems Biology and Biotechnology Specialization
Design systems-level experiments using appropriate cutting edge techniques, collect big data, and analyze and interpret small and big data sets quantitatively.
The Systems Biology Specialization covers the concepts and methodologies used in systems-level analysis of biomedical systems. Successful participants will learn how to use experimental, computational and mathematical methods in systems biology and how to design practical systems-level frameworks to address questions in a variety of biomedical fields. In the final Capstone Project, students will apply the methods they learned in five courses of specialization to work on a research project.
Frequently Asked Questions
When will I have access to the lectures and assignments?
Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
What is the refund policy?
Is financial aid available?
More questions? Visit the Learner Help Center.
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