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Phillip Compeau
and
Pavel Pevzner
Building a fully-fledged algorithm to assemble genomes from DNA fragments on a real dataset is an enormous challenge with major demand in the multi-billion dollar biotech industry.
In this capstone project, we will take the training wheels off and let you design your own optimized software program for genome sequencing.
Read more
Building a fully-fledged algorithm to assemble genomes from DNA fragments on a real dataset is an enormous challenge with major demand in the multi-billion dollar biotech industry.
In this capstone project, we will take the training wheels off and let you design your own optimized software program for genome sequencing.
Read more
Building a fully-fledged algorithm to assemble genomes from DNA fragments on a real dataset is an enormous challenge with major demand in the multi-billion dollar biotech industry.
In this capstone project, we will take the training wheels off and let you design your own optimized software program for genome sequencing.
This big data challenge will cover the entire MicroMasters program. After a brief introduction to the steps required to build a genome assembler, we will let you take steps on your own to start working with real data taken from a sequencing machine and see if you can design genome assembly software that can compete with popular software used in hundreds of sequencing labs around the world every day.
Register for this course and see more details by visiting:
OpenCourser.com/course/7ruhlq/algorithms
What's inside
Learning objectives
- Graph algorithms
- Algorithms for genome assembly
- Algorithm optimization
- Graph algorithms
- Algorithms for genome assembly
- Algorithm optimization
Syllabus
Traffic lights
Traffic lights
Read about what's good
what should give you pause and
possible dealbreakers
Examines graph algorithms, core for genome assembly
Explores algorithms for genome assembly, an industry standard
Develops algorithm optimization, a core skill for bioinformatics
Involves designing and implementing a genome assembler, a sought-after skill in biotech
Leverages real-world data, ensuring practical relevance
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Reviews summary
Practical capstone: genome assembly algorithms
Based on its design, students would likely describe this Algorithms and Data Structures Capstone course as highly demanding yet immensely rewarding. Learners would find the core strength in its hands-on project, focusing on graph algorithms and optimization for real genome assembly, which closely mirrors industry demands. While providing invaluable practical application for biotech and data science careers, students would likely highlight the steep learning curve and the expectation of a strong prior background in algorithms and data structures. It's designed to push you to design optimized software for complex challenges.
Challenges learners to design highly optimized software solutions.
"The focus on optimizing my code for performance and efficiency seems like a key, valuable takeaway."
"I expect to gain practical skills in making complex algorithms more efficient and competitive."
"Designing software that can compete with popular tools implies a deep dive into algorithm optimization."
Applies theory to a significant real-world problem.
"I expect to apply complex algorithms to real genomic data, which is incredibly insightful."
"The hands-on work with real datasets makes the learning experience highly practical and relevant."
"This course bridges the gap between theoretical knowledge and real-world application in bioinformatics."
Requires a solid background in algorithms and data structures.
"I believe I'll need to have my core algorithms and programming knowledge very sharp for this capstone."
"This course is likely best suited for those who have completed prior advanced courses in computer science."
"Don't expect much hand-holding on foundational concepts; it's a capstone, not an introductory course."
A rigorous capstone requiring significant dedication and effort.
"I anticipate this course will be a true test of my algorithmic understanding and problem-solving skills."
"Learners should be prepared to invest considerable time into independent problem-solving and debugging."
"The complexity of genome assembly and optimization implies a very steep learning curve for many."
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 Algorithms and Data Structures Capstone with these
activities:
Explore the edX course platform
Show steps
Start learning about the course platform to familiarize yourself with the course structure and tools.
Browse courses on
edX
Show steps
-
Create an edX account
-
Explore the course interface
-
Review the course syllabus
Build a simple genome assembly algorithm
Show steps
Develop a basic understanding of genome assembly algorithms by building your own
Browse courses on
Genome Assembly
Show steps
-
Choose a programming language and framework
-
Implement the De Bruijn graph algorithm
-
Test your algorithm on a small dataset
-
Analyze the results and identify areas for improvement
Solve graph algorithm problems
Show steps
Strengthen your understanding of graph algorithms by solving practice problems.
Browse courses on
Graph Algorithms
Show steps
-
Identify a problem-solving platform
-
Start solving problems of varying difficulty levels
-
Review your solutions and identify areas for improvement
Five other activities
Expand to see all activities and additional details
Show all eight activities
Attend a workshop on genome assembly
Show steps
Expand your knowledge and connect with experts in the field by attending a workshop on genome assembly.
Browse courses on
Genome Assembly
Show steps
-
Identify and register for a relevant workshop
-
Attend the workshop and actively participate in discussions
-
Follow up with the organizers or speakers to continue learning
Read 'Algorithms for DNA Sequencing' by Pavel Pevzner
Show steps
Gain a deeper understanding of genome assembly algorithms from a leading expert in the field.
View
An Introduction to Bioinformatics Algorithms...
on Amazon
Show steps
-
Identify the key concepts covered in the book
-
Read and take notes on the relevant chapters
-
Summarize the main takeaways
Mentor junior students in genome assembly
Show steps
Reinforce your understanding of genome assembly by mentoring others.
Browse courses on
Genome Assembly
Show steps
-
Identify opportunities to mentor junior students
-
Provide guidance and support on genome assembly concepts
-
Evaluate student progress and provide constructive feedback
Create a presentation on genome assembly optimization
Show steps
Demonstrate your understanding of genome assembly optimization by creating a presentation.
Browse courses on
Genome Assembly
Show steps
-
Research different genome assembly optimization techniques
-
Design and create a presentation that showcases your findings
-
Present your findings to your peers or instructors
Contribute to an open-source genome assembly project
Show steps
Gain practical experience and contribute to the field by participating in an open-source genome assembly project.
Browse courses on
Genome Assembly
Show steps
-
Identify a relevant open-source project
-
Review the project documentation and contribute code
-
Participate in project discussions and provide feedback
Explore the edX course platform
Show steps
Start learning about the course platform to familiarize yourself with the course structure and tools.
Browse courses on
edX
Show steps
Show steps
Show steps
- Create an edX account
- Explore the course interface
- Review the course syllabus
Build a simple genome assembly algorithm
Show steps
Develop a basic understanding of genome assembly algorithms by building your own
Browse courses on
Genome Assembly
Show steps
Show steps
Show steps
- Choose a programming language and framework
- Implement the De Bruijn graph algorithm
- Test your algorithm on a small dataset
- Analyze the results and identify areas for improvement
Solve graph algorithm problems
Show steps
Strengthen your understanding of graph algorithms by solving practice problems.
Browse courses on
Graph Algorithms
Show steps
Show steps
Show steps
- Identify a problem-solving platform
- Start solving problems of varying difficulty levels
- Review your solutions and identify areas for improvement
Five other activities
Expand to see all activities and additional details
Show all eight activities
Attend a workshop on genome assembly
Show steps
Expand your knowledge and connect with experts in the field by attending a workshop on genome assembly.
Browse courses on
Genome Assembly
Show steps
Show steps
Show steps
- Identify and register for a relevant workshop
- Attend the workshop and actively participate in discussions
- Follow up with the organizers or speakers to continue learning
Read 'Algorithms for DNA Sequencing' by Pavel Pevzner
Show steps
Gain a deeper understanding of genome assembly algorithms from a leading expert in the field.
View
An Introduction to Bioinformatics Algorithms...
on Amazon
Show steps
Show steps
Show steps
- Identify the key concepts covered in the book
- Read and take notes on the relevant chapters
- Summarize the main takeaways
Mentor junior students in genome assembly
Show steps
Reinforce your understanding of genome assembly by mentoring others.
Browse courses on
Genome Assembly
Show steps
Show steps
Show steps
- Identify opportunities to mentor junior students
- Provide guidance and support on genome assembly concepts
- Evaluate student progress and provide constructive feedback
Create a presentation on genome assembly optimization
Show steps
Demonstrate your understanding of genome assembly optimization by creating a presentation.
Browse courses on
Genome Assembly
Show steps
Show steps
Show steps
- Research different genome assembly optimization techniques
- Design and create a presentation that showcases your findings
- Present your findings to your peers or instructors
Contribute to an open-source genome assembly project
Show steps
Gain practical experience and contribute to the field by participating in an open-source genome assembly project.
Browse courses on
Genome Assembly
Show steps
Show steps
Show steps
- Identify a relevant open-source project
- Review the project documentation and contribute code
- Participate in project discussions and provide feedback
Career center
Learners who complete Algorithms and Data Structures Capstone will develop knowledge and skills
that may be useful to these careers:
Bioinformatician
Bioinformatician
Your work may include developing and publishing machine learning algorithms for sequencing and assembling complex microbial communities. Expertise in writing efficient algorithms in C++ to solve large-scale genomic problems would be important. You should have a strong background in algorithm design for sequence assembly and genomics. This course will provide you with a foundation in designing algorithms for genome assembly. You will also learn graph algorithms.
Biomedical Engineer
Biomedical Engineer
Biomedical engineers collaborate with doctors, biologists, and computer scientists to solve problems in biology and health. You may design medical devices, imaging systems, or computer simulations, and then test them on cells and living organisms. You may also work on developing algorithms.
Computer Scientist
Computer Scientist
The primary research method of computer science is to design, develop, implement and apply computer software and hardware systems. This course will teach you the graph algorithms and algorithms for genome assembly used by computer scientists.
Computational Biologist
Computational Biologist
Computational biologists use tools like bioinformatics, statistical modeling, and machine learning to analyze biological data. These tools can be used to better understand biological processes, create models to predict future events, and diagnose diseases. This course will provide you with the essential graph algorithms and algorithms for genome assembly needed to be successful as a computational biologist.
Data Analyst
Data Analyst
Data analysts collect, clean, and analyze data. They may also create visualizations to help people understand data. This course will teach you the data analysis algorithms used by data analysts.
Data Scientist
Data Scientist
Data scientists use scientific methods to extract knowledge from data, which they may use to make predictions or solve problems. This course will teach you the graph algorithms and algorithms for genome assembly that are used by data scientists.
Genome Bioinformatician
Genome Bioinformatician
Genome bioinformaticians play a vital role in modern medical research. They develop and apply bioinformatics tools such as sequence assembly and alignment algorithms to genome data. As a genome bioinformatician, you will be responsible for developing and implementing algorithms for genome assembly. This course will provide you with a foundation in graph algorithms and algorithms for genome assembly, which are essential for success in this role.
Genomics Specialist
Genomics Specialist
Genomics specialists are responsible for analyzing and interpreting genomic data. This may involve developing and using algorithms for genome assembly. This course will provide you with a solid foundation in the graph algorithms and algorithms for genome assembly that are used by genomics specialists.
Machine Learning Engineer
Machine Learning Engineer
Machine learning engineers use machine learning algorithms to solve problems. They may also develop and implement new machine learning algorithms. This course will teach you graph algorithms and algorithms for genome assembly that are used by machine learning engineers.
Operations Research Analyst
Operations Research Analyst
Operations research analysts use mathematical and analytical methods to solve problems in business and industry. These methods may include algorithm optimization. This course will teach you the algorithm optimization techniques used by operations research analysts.
Research Scientist
Research Scientist
Research scientists conduct research in a variety of fields, including computer science, biology, and engineering. Research scientists may develop and use algorithms for genome assembly. This course will provide you with the graph algorithms and algorithms for genome assembly that are essential for research in this field.
Software Developer
Software Developer
Software developers design, develop, and implement software. They may also work on developing algorithms. This course will teach you the graph algorithms and algorithms for genome assembly used by software developers.
Systems Analyst
Systems Analyst
Systems analysts design, develop, and implement computer systems. They may also work on developing algorithms. This course will teach you the graph algorithms and algorithms for genome assembly used by systems analysts.
Web Developer
Web Developer
Web developers design, develop, and implement websites. They may also work on developing algorithms. This course will teach you the graph algorithms and algorithms for genome assembly used by web developers.
Database Administrator
Database Administrator
Database administrators design, develop, and implement databases. They may also work on developing algorithms. This course will teach you the graph algorithms and algorithms for genome assembly used by database administrators.
For more career information including salaries, visit:
OpenCourser.com/course/7ruhlq/algorithms
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
Algorithms and Data Structures Capstone.
Comprehensive guide to bioinformatics algorithms, with a strong focus on genome assembly. It covers the fundamental concepts and techniques used in genome assembly, and provides detailed descriptions of popular software tools.
Comprehensive guide to data structures and algorithms in Java. It covers a wide range of topics, including basic data structures, sorting algorithms, and graph algorithms.
Classic textbook on algorithms. It covers a wide range of topics, including graph algorithms, string algorithms, and NP-completeness.
Practical guide to bioinformatics data skills. It covers a wide range of topics, including data management, data analysis, and data visualization.
Practical guide to bioinformatics programming using Python. It covers a wide range of topics, including data structures, algorithms, and machine learning.
Comprehensive guide to data analysis for the life sciences. It covers a wide range of topics, including statistical methods, machine learning, and data visualization.
Concise guide to bioinformatics. It covers a wide range of topics, including DNA sequencing, RNA sequencing, and protein sequencing.
Gentle introduction to bioinformatics. It covers a wide range of topics, including DNA sequencing, RNA sequencing, and protein sequencing.
Classic textbook on molecular biology. It covers a wide range of topics, including DNA structure and function, gene expression, and protein synthesis.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/7ruhlq/algorithms
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Effort
8 to 10 hours per week for 4 weeks
Level
Intermediate
Via
edX
Institution
The University of California, San Diego
Instructors
Phillip Compeau
Pavel Pevzner
Language
English
Transcript
English
This course belongs to a
collection
called
Algorithms and Data Structures. It's comprised of nine courses:
- Algorithmic Design and Techniques
- Data Structures Fundamentals
- Graph Algorithms
- NP-Complete Problems
- String Processing and Pattern Matching Algorithms
- Dynamic Programming: Applications In Machine Learning and Genomics
- Graph Algorithms in Genome Sequencing
- Introduction to Algorithms
- Algorithms and Data Structures Capstone (viewing)
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