A Geometrical Approach to Genome Analysis: Skew & Z-Curve from Coursera

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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!

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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

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in A Geometrical Approach to Genome Analysis: Skew & Z-Curve with these activities:

Review Biology

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This course covers topics related to biology, including molecular biology and genetics. A refresher course in biology will help reinforce course material.

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Review basic biology concepts
Review molecular biology and genetics

Review Python

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Python is the main programming language used in this course. It is necessary to review Python syntax before taking this course.

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Review Python syntax
Practice writing Python code

Review General Python

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Python is the language used in this course. Having more knowledge on Python can only be beneficial to complete this course.

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Review basic Python syntax
Review basic Python data structures
Review basic Python programming concepts

Nine other activities

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Practice Python programming drills

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Regular practice can reinforce understanding and increase proficiency in Python programming.

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Find and complete online Python coding challenges
Work through Python coding exercises

Review 'Bioinformatics and Functional Genomics' by Jonathan Pevsner

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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

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Read and summarize key chapters
Identify and research unfamiliar concepts

Learn about Python libraries

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This course uses several Python libraries, including NumPy, Matplotlib, and Tkinter. Familiarity with these libraries will enhance comprehension of course material.

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Find tutorials on NumPy
Find tutorials on Matplotlib
Find tutorials on Tkinter

Compile and Review Course Materials

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Regularly reviewing course materials can improve retention and understanding.

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Organize and review notes, assignments, and quizzes
Identify areas for improvement and seek additional resources

Practice Python coding

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Regular practice with Python coding will help improve understanding of course materials.

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Find coding drills
Find coding exercises

Start a Complete Viral Genome Analysis Project

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This project will allow students to apply and test the skills and knowledge acquired from this course.

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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

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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.

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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

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Creating a visual guide will help solidify understanding of bioinformatics concepts and improve communication skills.

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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

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Contributing to an open-source project provides practical experience and exposure to real-world bioinformatics applications.

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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 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.

See salaries and explore the career path for Genome Analyst

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.

See salaries and explore the career path for Computational Biologist

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.

See salaries and explore the career path for Bioinformatician

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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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