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Ben Langmead, PhD
and
Jacob Pritt
We will learn computational methods -- algorithms and data structures -- for analyzing DNA sequencing data. We will learn a little about DNA, genomics, and how DNA sequencing is used. We will use Python to implement key algorithms and data structures and to analyze real genomes and DNA sequencing datasets.
Register for this course and see more details by visiting:
OpenCourser.com/course/1bkc6g/algorithms
What's inside
Syllabus
DNA sequencing, strings and matching
This module we begin our exploration of algorithms for analyzing DNA sequencing data. We'll discuss DNA sequencing technology, its past and present, and how it works.
Read more
Syllabus
DNA sequencing, strings and matching
This module we begin our exploration of algorithms for analyzing DNA sequencing data. We'll discuss DNA sequencing technology, its past and present, and how it works.
Read more
Preprocessing, indexing and approximate matching
In this module, we learn useful and flexible new algorithms for solving the exact and approximate matching problems. We'll start by learning Boyer-Moore, a fast and very widely used algorithm for exact matching
Edit distance, assembly, overlaps
This week we finish our discussion of read alignment by learning about algorithms that solve both the edit distance problem and related biosequence analysis problems, like global and local alignment.
Algorithms for assembly
In the last module we began our discussion of the assembly problem and we saw a couple basic principles behind it. In this module, we'll learn a few ways to solve the alignment problem.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Taught by instructors who are recognized for their work in the field of bioinformatics
Explores algorithms and data structures specifically designed for analyzing DNA sequencing data, which is fundamental in the field of genomics and personalized medicine
Develops skills in Python programming, specifically for bioinformatics applications, which are valuable in both research and industry
Provides a foundation in the principles of DNA sequencing and analysis, which is essential for researchers in genetics, biotechnology, and related fields
Requires learners to have a basic understanding of Python and some familiarity with biology and molecular biology concepts, which may be a barrier for complete beginners
Focuses primarily on computational methods and does not delve deeply into the biological implications of DNA sequencing, which may be limiting for those seeking a comprehensive understanding of the field
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Save Algorithms for DNA Sequencing to your list so you can find it easily later:
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Reviews summary
Quality dna sequencing algorithms course
Learners say this well-taught and challenging Algorithms for DNA Sequencing course is a series highlight. Students call out the course's excellent lectures, helpful assignments, and engaging labs for helping them build a strong understanding of the algorithms used in DNA sequencing. The course assumes some Python experience, but instructors are unresponsive to students without it.
Lectures and assignments are interesting and helpful.
"I found the lectures and the assignments to be very helpful and interesting."
Course is challenging but doable.
"Unlike some of the other courses in the Genomic Data Science Specialization, which have been shallow or poorly taught, this course is challenging (but not undoable) and the lectures are very well organized."
Course assumes Python knowledge.
"This course has a serious problem for anyone who has only taken the previous Introduction to Python course."
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 for DNA Sequencing with these
activities:
Review Python programming
Show steps
Ensure a solid foundation in Python programming language for successful implementation of algorithms and data structures used to analyze DNA sequencing data
Browse courses on
Python Programming
Show steps
-
Review the basics of Python syntax, such as data types, variables, and control flow.
-
Practice writing simple Python programs.
Read 'Bioinformatics Algorithms: Techniques and Applications'
Show steps
Gain a comprehensive understanding of the algorithms and data structures used in bioinformatics and genomics, providing a foundational knowledge base
View
An Introduction to Bioinformatics Algorithms...
on Amazon
Show steps
-
Read the chapters relevant to the course material.
-
Work through the practice exercises in the book.
Practice DNA sequence alignment
Show steps
Reinforce concepts by practicing the alignment of DNA sequences to identify regions of similarity or difference
Show steps
-
Use a sequence alignment tool, such as BLAST or ClustalW, to align two or more DNA sequences.
-
Identify the regions of similarity and difference between the sequences.
-
Interpret the results of the alignment to determine the evolutionary relationship between the sequences.
Show all three activities
Review Python programming
Show steps
Ensure a solid foundation in Python programming language for successful implementation of algorithms and data structures used to analyze DNA sequencing data
Browse courses on
Python Programming
Show steps
Show steps
Show steps
- Review the basics of Python syntax, such as data types, variables, and control flow.
- Practice writing simple Python programs.
Read 'Bioinformatics Algorithms: Techniques and Applications'
Show steps
Gain a comprehensive understanding of the algorithms and data structures used in bioinformatics and genomics, providing a foundational knowledge base
View
An Introduction to Bioinformatics Algorithms...
on Amazon
Show steps
Show steps
Show steps
- Read the chapters relevant to the course material.
- Work through the practice exercises in the book.
Practice DNA sequence alignment
Show steps
Reinforce concepts by practicing the alignment of DNA sequences to identify regions of similarity or difference
Show steps
Show steps
Show steps
- Use a sequence alignment tool, such as BLAST or ClustalW, to align two or more DNA sequences.
- Identify the regions of similarity and difference between the sequences.
- Interpret the results of the alignment to determine the evolutionary relationship between the sequences.
Show all three activities
Career center
Learners who complete Algorithms for DNA Sequencing will develop knowledge and skills
that may be useful to these careers:
Biostatistician
Biostatistician
In this role, you would be involved in designing studies, collecting and analyzing data, and interpreting results. You would also be responsible for communicating your findings to a variety of audiences.
Taking this course would provide you with a strong foundation in the computational methods used to analyze DNA sequencing data. This knowledge would be invaluable in your work as a Biostatistician, as you would be able to use these methods to design and conduct studies that are more efficient and accurate.
Computational Biologist
Computational Biologist
In this role, you would be responsible for developing and applying computational methods to solve problems in biology. You would use your skills in computer science, biology, and mathematics to create models, algorithms, and software to analyze and interpret biological data.
Taking this course would provide you with a strong foundation in the computational methods used to analyze DNA sequencing data. This knowledge would be invaluable in your work as a Computational Biologist, as you would be able to use these methods to develop new algorithms and software to solve important problems in biology.
Software Engineer
Software Engineer
Software Engineers design, develop, and test software applications.
Taking this course would provide you with a strong foundation in the computational methods used to analyze DNA sequencing data. This knowledge would be invaluable in your work as a Software Engineer, as you would be able to use these methods to develop new algorithms and software to solve problems in a variety of fields.
Genomics Scientist
Genomics Scientist
Genomics Scientists use computational methods to analyze and interpret genomic data.
Taking this course would provide you with a strong foundation in the computational methods used to analyze DNA sequencing data. This knowledge would be invaluable in your work as a Genomics Scientist, as you would be able to use these methods to develop new algorithms and software to solve important problems in genomics.
Geneticist
Geneticist
Geneticists study the structure and function of genes and their role in heredity and disease.
Taking this course would provide you with a strong foundation in the computational methods used to analyze DNA sequencing data. This knowledge would be invaluable in your work as a Geneticist, as you would be able to use these methods to identify and characterize new genes and mutations associated with disease.
Research Scientist
Research Scientist
Research Scientists conduct research to develop new products and technologies.
Taking this course would provide you with a strong foundation in the computational methods used to analyze DNA sequencing data. This knowledge would be invaluable in your work as a Research Scientist, as you would be able to use these methods to develop new algorithms and software to solve important problems in a variety of fields.
Data Scientist
Data Scientist
These professionals use their skills in mathematics, statistics, and computer science to extract insights from data.
Taking this course would provide you with a strong foundation in the computational methods used to analyze DNA sequencing data. This knowledge would be invaluable in your work as a Data Scientist, as you would be able to use these methods to develop new algorithms and software to solve problems in a variety of fields, including healthcare, finance, and manufacturing.
Medical Scientist
Medical Scientist
Medical Scientists conduct research to develop new treatments and cures for diseases.
Taking this course would provide you with a strong foundation in the computational methods used to analyze DNA sequencing data. This knowledge would be invaluable in your work as a Medical Scientist, as you would be able to use these methods to identify new targets for drug development and to develop new diagnostic tests.
Research Associate
Research Associate
Research Associates conduct research under the supervision of a senior scientist.
Taking this course would provide you with a strong foundation in the computational methods used to analyze DNA sequencing data. This knowledge would be invaluable in your work as a Research Associate, as you would be able to use these methods to develop new research projects and to publish your findings in peer-reviewed journals.
Quality Control Analyst
Quality Control Analyst
Quality Control Analysts ensure that products and services meet quality standards.
Taking this course would provide you with a strong foundation in the computational methods used to analyze DNA sequencing data. This knowledge would be invaluable in your work as a Quality Control Analyst, as you would be able to use these methods to develop new quality control procedures and to ensure that DNA sequencing data is accurate and reliable.
Postdoctoral Researcher
Postdoctoral Researcher
Postdoctoral Researchers conduct research under the supervision of a senior scientist.
Taking this course would provide you with a strong foundation in the computational methods used to analyze DNA sequencing data. This knowledge would be invaluable in your work as a Postdoctoral Researcher, as you would be able to use these methods to develop new research projects and to publish your findings in peer-reviewed journals.
Laboratory Technician
Laboratory Technician
Laboratory Technicians conduct experiments, analyze data, and maintain laboratory equipment.
Taking this course would provide you with a strong foundation in the computational methods used to analyze DNA sequencing data. This knowledge would be invaluable in your work as a Laboratory Technician, as you would be able to use these methods to develop new protocols and assays for DNA sequencing.
Molecular Biologist
Molecular Biologist
Molecular Biologists study the structure and function of molecules, including DNA, RNA, and proteins.
Taking this course would provide you with a strong foundation in the computational methods used to analyze DNA sequencing data. This knowledge would be invaluable in your work as a Molecular Biologist, as you would be able to use these methods to identify and characterize new genes and mutations associated with disease.
Physician
Physician
Physicians diagnose and treat diseases. They also provide preventive care and counseling to their patients.
Taking this course may provide you with a better understanding of the computational methods used to analyze DNA sequencing data. This knowledge may be helpful in your work as a Physician, as you may be able to use these methods to identify and diagnose diseases more accurately.
Project Manager
Project Manager
Project Managers plan, execute, and close out projects. They also manage the project team and budget.
Taking this course may provide you with a better understanding of the computational methods used to analyze DNA sequencing data. This knowledge may be helpful in your work as a Project Manager, as you may be able to use these methods to manage projects more effectively.
For more career information including salaries, visit:
OpenCourser.com/course/1bkc6g/algorithms
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
Algorithms for DNA Sequencing.
Provides a comprehensive overview of fundamental algorithms and approaches used in bioinformatics.
Provides a solid foundation in the algorithmic techniques and foundations of biological sequence analysis.
Introduces the field of computational biology from a statistical mechanics perspective.
Provides a practical guide to bioinformatics techniques and tools.
Provides an introductory overview of bioinformatics concepts and techniques.
Provides an introduction to bioinformatics and functional genomics.
Provides a foundational introduction to Python programming and scientific computing.
Provides a practical introduction to Python for data analysis and data manipulation.
Save
Provides a comprehensive overview of deep learning.
This classic textbook provides a comprehensive overview of algorithms and data structures.
This textbook provides a practical introduction to data structures and algorithms using Java.
This introductory textbook provides a broad overview of computational molecular biology.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/1bkc6g/algorithms
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Institution
Johns Hopkins University
Instructors
Ben Langmead, PhD
Jacob Pritt
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English
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Good to know
Taught by instructors who are recognized for their work in the field of bioinformatics
Explores algorithms and data structures specifically designed for analyzing DNA sequencing data, which is fundamental in the field of genomics and personalized medicine
Develops skills in Python programming, specifically for bioinformatics applications, which are valuable in both research and industry
Provides a foundation in the principles of DNA sequencing and analysis, which is essential for researchers in genetics, biotechnology, and related fields
Requires learners to have a basic understanding of Python and some familiarity with biology and molecular biology concepts, which may be a barrier for complete beginners
Focuses primarily on computational methods and does not delve deeply into the biological implications of DNA sequencing, which may be limiting for those seeking a comprehensive understanding of the field
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