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Usama A. F. Khalil
In this 1-hour long project-based course, you will learn how to analyze a complete viral genome using geometrical methods (skews and Z-curve), 2D- and 3D-plotting in Python, and how to use some important Python libraries (like Tkinter, Matplotlib, and NumPy) helping you accomplish this. You will also learn about the genomes of some viruses including, Corona, SARS, HIV, Zika, Nidovirous, and rubella viruses.
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Syllabus
A Geometrical Approach to Genome Analysis: Skew & Z-Curve
A Geometrical Approach to Genome Analysis: Skew & Z-Curve using Python Project! You’re joining thousands of learners currently enrolled in the Rhyme guided project program. I'm excited to have you in the class and look forward to your contributions to the learning community. To begin, I recommend taking a few minutes to explore the course site. Review the material we’ll cover during the project, and preview the assignments you’ll need to complete to pass the course. Click Discussions to see forums where you can discuss the course material with fellow students taking the class. By the end of this project, you will create a Python program using a jupyter interface that analyzes a complete viral genome using geometrical methods (skews and Z-curve). You will use complete genome sequences for many viruses including, Corona, SARS, HIV, Zika, Planarian Nidovirous, and rubella viruses. Finally, you will learn how to build a PDF file to save all your analysis data and graphs. Along the way, you will learn how to plot in 2D and 3D graphs in Python language. If you have questions about course content, please post them in the forums to get help from others in the course community. For technical problems with the Coursera platform, visit the Learner Help Center. Good luck as you get started and I hope you enjoy the course!
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Introduces learners to some important Python libraries (like Tkinter, Matplotlib, and NumPy) and teaches how these libraries can be used for genome analysis using geometrical methods
Provides practical experience in analyzing complete viral genomes, which prepares students for entry-level roles in bioinformatics
Uses a Jupyter interface, which is a popular environment for data analysis and visualization, giving learners transferable skills for data science roles
Covers a variety of viruses, including Corona, SARS, HIV, Zika, Nidovirous, and rubella viruses, providing learners with a comprehensive understanding of viral genome analysis
Assumes no prior knowledge in viral genomics, making it accessible to beginners in the field
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Activities
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in A Geometrical Approach to Genome Analysis: Skew & Z-Curve with these
activities:
Review Biology
Show steps
This course covers topics related to biology, including molecular biology and genetics. A refresher course in biology will help reinforce course material.
Browse courses on
Biology
Show steps
-
Review basic biology concepts
-
Review molecular biology and genetics
Review Python
Show steps
Python is the main programming language used in this course. It is necessary to review Python syntax before taking this course.
Browse courses on
Programming
Show steps
-
Review Python syntax
-
Practice writing Python code
Review General Python
Show steps
Python is the language used in this course. Having more knowledge on Python can only be beneficial to complete this course.
Browse courses on
Python
Show steps
-
Review basic Python syntax
-
Review basic Python data structures
-
Review basic Python programming concepts
Nine other activities
Expand to see all activities and additional details
Show all 12 activities
Practice Python programming drills
Show steps
Regular practice can reinforce understanding and increase proficiency in Python programming.
Browse courses on
Python
Show steps
-
Find and complete online Python coding challenges
-
Work through Python coding exercises
Review 'Bioinformatics and Functional Genomics' by Jonathan Pevsner
Show steps
This book provides a comprehensive overview of bioinformatics and functional genomics, complementing the topics covered in the course.
View
Bioinformatics and Functional Genomics
on Amazon
Show steps
-
Read and summarize key chapters
-
Identify and research unfamiliar concepts
Learn about Python libraries
Show steps
This course uses several Python libraries, including NumPy, Matplotlib, and Tkinter. Familiarity with these libraries will enhance comprehension of course material.
Browse courses on
Python
Show steps
-
Find tutorials on NumPy
-
Find tutorials on Matplotlib
-
Find tutorials on Tkinter
Compile and Review Course Materials
Show steps
Regularly reviewing course materials can improve retention and understanding.
Browse courses on
Review
Show steps
-
Organize and review notes, assignments, and quizzes
-
Identify areas for improvement and seek additional resources
Practice Python coding
Show steps
Regular practice with Python coding will help improve understanding of course materials.
Browse courses on
Python
Show steps
-
Find coding drills
-
Find coding exercises
Start a Complete Viral Genome Analysis Project
Show steps
This project will allow students to apply and test the skills and knowledge acquired from this course.
Browse courses on
Analysis
Show steps
-
Gather data for a complete viral genome
-
Choose and apply the appropriate analysis methods
-
Visualize and interpret the results
-
Write a report summarizing the findings
Follow tutorials for DNA Sequence Alignments
Show steps
DNA sequence alignments are an important technique used in this course to compare and identify similar genomes. Practicing this will help increase a student's skill.
Browse courses on
Alignment
Show steps
-
Find and select tutorials on DNA sequence alignments
-
Follow the tutorials step-by-step
-
Practice aligning DNA sequences using the techniques learned
Create a Visual Guide to Bioinformatics for Beginners
Show steps
Creating a visual guide will help solidify understanding of bioinformatics concepts and improve communication skills.
Browse courses on
Bioinformatics
Show steps
-
Research and gather information on bioinformatics basics
-
Design and create visual aids, such as diagrams, charts, and infographics
-
Organize and present the information in a clear and concise manner
Contribute to an Open-Source Bioinformatics Project
Show steps
Contributing to an open-source project provides practical experience and exposure to real-world bioinformatics applications.
Browse courses on
Bioinformatics
Show steps
-
Identify and select an open-source bioinformatics project
-
Review the project's documentation and codebase
-
Contribute code, bug fixes, or documentation improvements
Review Biology
Show steps
This course covers topics related to biology, including molecular biology and genetics. A refresher course in biology will help reinforce course material.
Browse courses on
Biology
Show steps
Show steps
Show steps
- Review basic biology concepts
- Review molecular biology and genetics
Review Python
Show steps
Python is the main programming language used in this course. It is necessary to review Python syntax before taking this course.
Browse courses on
Programming
Show steps
Show steps
Show steps
- Review Python syntax
- Practice writing Python code
Review General Python
Show steps
Python is the language used in this course. Having more knowledge on Python can only be beneficial to complete this course.
Browse courses on
Python
Show steps
Show steps
Show steps
- Review basic Python syntax
- Review basic Python data structures
- Review basic Python programming concepts
Nine other activities
Expand to see all activities and additional details
Show all 12 activities
Practice Python programming drills
Show steps
Regular practice can reinforce understanding and increase proficiency in Python programming.
Browse courses on
Python
Show steps
Show steps
Show steps
- Find and complete online Python coding challenges
- Work through Python coding exercises
Review 'Bioinformatics and Functional Genomics' by Jonathan Pevsner
Show steps
This book provides a comprehensive overview of bioinformatics and functional genomics, complementing the topics covered in the course.
View
Bioinformatics and Functional Genomics
on Amazon
Show steps
Show steps
Show steps
- Read and summarize key chapters
- Identify and research unfamiliar concepts
Learn about Python libraries
Show steps
This course uses several Python libraries, including NumPy, Matplotlib, and Tkinter. Familiarity with these libraries will enhance comprehension of course material.
Browse courses on
Python
Show steps
Show steps
Show steps
- Find tutorials on NumPy
- Find tutorials on Matplotlib
- Find tutorials on Tkinter
Compile and Review Course Materials
Show steps
Regularly reviewing course materials can improve retention and understanding.
Browse courses on
Review
Show steps
Show steps
Show steps
- Organize and review notes, assignments, and quizzes
- Identify areas for improvement and seek additional resources
Practice Python coding
Show steps
Regular practice with Python coding will help improve understanding of course materials.
Browse courses on
Python
Show steps
Show steps
Show steps
- Find coding drills
- Find coding exercises
Start a Complete Viral Genome Analysis Project
Show steps
This project will allow students to apply and test the skills and knowledge acquired from this course.
Browse courses on
Analysis
Show steps
Show steps
Show steps
- Gather data for a complete viral genome
- Choose and apply the appropriate analysis methods
- Visualize and interpret the results
- Write a report summarizing the findings
Follow tutorials for DNA Sequence Alignments
Show steps
DNA sequence alignments are an important technique used in this course to compare and identify similar genomes. Practicing this will help increase a student's skill.
Browse courses on
Alignment
Show steps
Show steps
Show steps
- Find and select tutorials on DNA sequence alignments
- Follow the tutorials step-by-step
- Practice aligning DNA sequences using the techniques learned
Create a Visual Guide to Bioinformatics for Beginners
Show steps
Creating a visual guide will help solidify understanding of bioinformatics concepts and improve communication skills.
Browse courses on
Bioinformatics
Show steps
Show steps
Show steps
- Research and gather information on bioinformatics basics
- Design and create visual aids, such as diagrams, charts, and infographics
- Organize and present the information in a clear and concise manner
Contribute to an Open-Source Bioinformatics Project
Show steps
Contributing to an open-source project provides practical experience and exposure to real-world bioinformatics applications.
Browse courses on
Bioinformatics
Show steps
Show steps
Show steps
- Identify and select an open-source bioinformatics project
- Review the project's documentation and codebase
- Contribute code, bug fixes, or documentation improvements
Career center
Learners who complete A Geometrical Approach to Genome Analysis: Skew & Z-Curve will develop knowledge and skills
that may be useful to these careers:
Genome Analyst
Genome Analyst
Genome analysts study the structure, function, and evolution of genomes. This course introduces you to powerful techniques for analyzing genome sequences, including skew and Z-curve analysis. By learning to use Python programming for genome analysis, you can effectively extract valuable information from complex genomic data. The course also covers important Python libraries such as NumPy and Matplotlib, which are essential tools for genome analysts.
Computational Biologist
Computational Biologist
Computational biologists develop and apply computational tools and techniques to understand biological systems. This course provides hands-on experience with programming in Python, which is a widely used language in computational biology. You will also learn about fundamental techniques in analyzing biological data, such as skew and Z-curve analysis, which are commonly employed by computational biologists. By gaining these skills, you can effectively contribute to advancing our understanding of biological systems through computational approaches.
Bioinformatician
Bioinformatician
A bioinformatician uses computational tools to analyze biological data. This course can help build a foundation in using Python programming for analyzing such data. By learning how to plot 2D and 3D graphs using Python, you can effectively visualize and interpret the output of your analyses. Additionally, the course covers important Python libraries such as NumPy, which is widely used by bioinformaticians for scientific computing.
Data Scientist
Data Scientist
Data scientists analyze and interpret large datasets to extract insights and make informed decisions. This course provides a foundation in using Python for data analysis and visualization. By learning how to work with data, plot graphs, and use statistical techniques, you can build valuable skills that are in high demand for data scientists. Additionally, the course covers important Python libraries such as NumPy and Matplotlib, which are widely used in data science.
Machine Learning Engineer
Machine Learning Engineer
Machine learning engineers design, develop, and maintain machine learning systems. This course provides hands-on experience with programming in Python, which is widely used for machine learning. You will also learn about fundamental concepts and algorithms in machine learning, which are essential for building predictive models. By gaining these skills, you can effectively contribute to developing and deploying machine learning solutions to solve real-world problems.
Medical Physicist
Medical Physicist
Medical physicists apply physics principles to the field of medicine. This course introduces you to Python programming, which is increasingly used for data analysis and visualization in medical physics. By learning how to work with data, plot graphs, and use statistical techniques, you can build valuable skills for analyzing medical data. Additionally, the course covers important Python libraries such as NumPy and Matplotlib, which are widely used in medical physics.
Quantitative Analyst
Quantitative Analyst
Quantitative analysts use mathematical and statistical methods to analyze financial data. This course introduces you to Python programming, which is widely used for data analysis and visualization in finance. By learning how to work with data, plot graphs, and use statistical techniques, you can build valuable skills for analyzing financial data. Additionally, the course covers important Python libraries such as NumPy and Matplotlib, which are widely used in quantitative finance.
Statistician
Statistician
Statisticians collect, analyze, interpret, and present data. This course introduces you to Python programming, which is increasingly used for data analysis and visualization in statistics. By learning how to work with data, plot graphs, and use statistical techniques, you can build valuable skills for analyzing statistical data. Additionally, the course covers important Python libraries such as NumPy and Matplotlib, which are widely used in statistics.
Programmer
Programmer
Programmers design, develop, and maintain software systems. This course provides a foundation in programming using Python, which is a widely used language for software development. You will learn about fundamental programming concepts and techniques, such as data structures, algorithms, and object-oriented programming. By gaining these skills, you can effectively contribute to the development of software applications across various industries.
Software Engineer
Software Engineer
Software engineers design, develop, and maintain software systems. This course provides a foundation in programming using Python, which is a widely used language for software development. You will learn about fundamental programming concepts and techniques, such as data structures, algorithms, and object-oriented programming. By gaining these skills, you can effectively contribute to the development of software applications across various industries.
Web Developer
Web Developer
Web developers design, develop, and maintain websites. This course provides a foundation in programming using Python, which is increasingly used for developing web applications. You will learn about fundamental programming concepts and techniques, such as data structures, algorithms, and object-oriented programming. By gaining these skills, you can effectively contribute to the development of web applications across various industries.
Software Developer
Software Developer
Software developers design, develop, and maintain software systems. This course provides a foundation in programming using Python, which is a widely used language for software development. You will learn about fundamental programming concepts and techniques, such as data structures, algorithms, and object-oriented programming. By gaining these skills, you can effectively contribute to the development of software applications across various industries.
Systems Analyst
Systems Analyst
Systems analysts design, develop, and implement computer systems. This course provides a foundation in programming using Python, which is increasingly used for developing software systems. You will learn about fundamental programming concepts and techniques, such as data structures, algorithms, and object-oriented programming. By gaining these skills, you can effectively contribute to the development of software applications across various industries.
Researcher
Researcher
Researchers conduct scientific investigations to advance knowledge and understanding. This course introduces you to Python programming, which is increasingly used for data analysis and visualization in research. By learning how to work with data, plot graphs, and use statistical techniques, you can build valuable skills for analyzing research data. Additionally, the course covers important Python libraries such as NumPy and Matplotlib, which are widely used in research.
Teacher
Teacher
Teachers plan, prepare, and deliver educational instruction to students. This course provides hands-on experience with Python programming, which is increasingly used in teaching computer science and data science. By learning how to work with data, plot graphs, and use statistical techniques, you can build valuable skills for teaching students how to analyze data. Additionally, the course covers important Python libraries such as NumPy and Matplotlib, which are widely used in data science education.
For more career information including salaries, visit:
OpenCourser.com/course/oi0cyx/a
Reading list
We've selected 12 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
A Geometrical Approach to Genome Analysis: Skew & Z-Curve.
Provides a comprehensive introduction to computational molecular biology, covering topics such as DNA and protein sequence analysis, data visualization, and statistical methods. It valuable resource for students who want to learn the essential algorithms for working with biological data.
Provides a comprehensive introduction to molecular biology, covering topics such as DNA, RNA, and protein structure and function. It valuable resource for students who want to learn the essential concepts of molecular biology.
Provides a practical introduction to bioinformatics data analysis, covering topics such as DNA and protein sequence analysis, data visualization, and statistical methods. It valuable resource for students who want to learn the essential skills for working with biological data.
Provides a comprehensive introduction to algorithms for molecular biology, covering topics such as sequence alignment, phylogenetic analysis, and gene finding. It valuable resource for students who want to learn the essential algorithms for working with biological data.
Provides a comprehensive introduction to statistical methods in bioinformatics, covering topics such as DNA and protein sequence analysis, data visualization, and statistical methods. It valuable resource for students who want to learn the essential statistical methods for working with biological data.
Provides a comprehensive introduction to Python for bioinformatics, covering essential topics such as DNA and protein sequence analysis, data visualization, and statistical methods. It valuable resource for students who want to learn how to use Python for bioinformatics research.
Provides a comprehensive introduction to genomics, covering topics such as DNA sequencing, genome assembly, and comparative genomics. It valuable resource for students who want to learn the essential concepts of genomics.
Provides a comprehensive introduction to bioinformatics, covering topics such as DNA and protein sequence analysis, data visualization, and statistical methods. It valuable resource for students who want to learn the essential skills for working with biological data.
Provides a comprehensive introduction to bioinformatics and functional genomics, covering topics such as DNA and protein sequence analysis, data visualization, and statistical methods. It valuable resource for students who want to learn the essential skills for working with biological data.
Provides a comprehensive introduction to bioinformatics, covering topics such as DNA and protein sequence analysis, data visualization, and statistical methods. It valuable resource for students who want to learn the essential skills for working with biological data.
Provides a comprehensive introduction to mathematics for the life sciences, covering topics such as calculus, differential equations, and statistics. It valuable resource for students who want to learn the essential mathematical skills for working in the life sciences.
Provides a comprehensive introduction to Python for data analysis, covering essential libraries such as NumPy, Pandas, Matplotlib, and Seaborn. It valuable resource for learning the basics of data analysis in Python and would be a great starting point for students who are new to the field.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/oi0cyx/a
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Effort
About 60 minutes required for the project and 60 for the other materials (reading and assignment).
Level
Intermediate
Via
Coursera
Institution
Coursera Project Network
Instructor
Usama A. F. Khalil
Language
English
Good to know
Introduces learners to some important Python libraries (like Tkinter, Matplotlib, and NumPy) and teaches how these libraries can be used for genome analysis using geometrical methods
Provides practical experience in analyzing complete viral genomes, which prepares students for entry-level roles in bioinformatics
Uses a Jupyter interface, which is a popular environment for data analysis and visualization, giving learners transferable skills for data science roles
Covers a variety of viruses, including Corona, SARS, HIV, Zika, Nidovirous, and rubella viruses, providing learners with a comprehensive understanding of viral genome analysis
Assumes no prior knowledge in viral genomics, making it accessible to beginners in the field
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