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Algorithms for DNA Sequencing

Ben Langmead, PhD and Jacob Pritt

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.

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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.

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Traffic lights

Read about what's good

what should give you pause

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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Reviews summary

Algorithms for dna sequencing with python

According to learners, this course provides a positive`solid foundation` in algorithms essential for DNA sequencing data analysis. Many found the explanations of complex algorithms positive`clear and easy to follow`, effectively bridging the gap between computer science and biology. The positive`hands-on Python assignments` are frequently highlighted as a major strength, offering valuable practical experience implementing the discussed methods. Some students note that a warning`strong prerequisite knowledge` in algorithms, data structures, and Python is highly recommended to keep up with the pace and assignments. Overall, the course is considered positive`highly relevant` for those in computational biology or bioinformatics, offering skills directly applicable to real-world data.

Moves quickly through topics.

"The pace is quite fast and requires dedication to keep up with the material."

"Packed with information, moves quickly through complex modules."

"Need to stay on top of lectures and assignments to avoid falling behind."

"It's dense but covers a lot of ground quickly."

Sufficient biology context provided.

"Appreciated the explanations of biological concepts alongside the algorithms."

"Enough biology is covered to understand the data context and the problems being solved."

"Successfully bridges the gap between computer science methods and biological applications."

"Helps you understand *why* these algorithms are needed for DNA data."

Coding assignments solidify understanding.

"Implementing the algorithms in Python was the most valuable part of the course for me."

"The programming assignments were challenging but essential for truly understanding the methods."

"Great practice applying theoretical algorithms to real biological data using Python."

"The hands-on coding labs solidify the concepts better than just lectures."

Concepts are explained very clearly.

"The explanations of algorithms are very clear and intuitive..."

"The way the core algorithms were explained was incredibly clear and helpful."

"Professors explain complex concepts in a way that makes them easy to understand."

"Really helped me grasp the fundamental ideas behind sequence alignment and assembly algorithms."

Directly applicable to genomics data.

"The skills learned are immediately useful for analyzing DNA sequencing data in research or industry."

"Excellent course for anyone entering the field of bioinformatics or computational biology."

"Covers essential computational methods used constantly in genomics."

"Provides practical tools and understanding for working with real genomic datasets."

Need prior CS/Python knowledge.

"Highly recommend having a solid grasp of Python and data structures before starting this course."

"Found it quite challenging without a strong prior background in algorithms."

"The stated prerequisites might be a bit understated; knowledge of Python is crucial."

"Be prepared if you're not already comfortable with algorithm analysis and coding in Python."

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

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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

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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'

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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

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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

Career center

Learners who complete Algorithms for DNA Sequencing will develop knowledge and skills that may be useful to these careers:

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.

See salaries and explore the career path for Computational Biologist

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.

See salaries and explore the career path for Biostatistician

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.

See salaries and explore the career path for Geneticist

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.

See salaries and explore the career path for Genomics Scientist

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.

See salaries and explore the career path for Software Engineer

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.

See salaries and explore the career path for Data 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.

See salaries and explore the career path for Research 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.

See salaries and explore the career path for Medical Scientist

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.

See salaries and explore the career path for Laboratory Technician

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.

See salaries and explore the career path for Molecular Biologist

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.

See salaries and explore the career path for Postdoctoral Researcher

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.

See salaries and explore the career path for Quality Control Analyst

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.

See salaries and explore the career path for Research Associate

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.

See salaries and explore the career path for Physician

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.

See salaries and explore the career path for Project Manager

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.

Cover image

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Bioinformatics Algorithms

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Provides a comprehensive overview of fundamental algorithms and approaches used in bioinformatics.

BIOINFORMATICS ALGORITHMS

BIOINFORMATICS ALGORITHMS,VOL.II

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Biological Sequence Analysis

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Provides a solid foundation in the algorithmic techniques and foundations of biological sequence analysis.

Biological Sequence Analysis: Probabilistic Models...

Biological Sequence Analysis: Probabilistic Models...

Biological Sequence Analysis: Probabilistic Models...

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Bioinformatics, second edition

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Introduces the field of computational biology from a statistical mechanics perspective.

Bioinformatics: The Machine Learning Approach,...

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BIOINFORMATICS: A PRACTICAL GUIDE TO THE ANALYSIS...

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Provides a practical guide to bioinformatics techniques and tools.

Bioinformatics: A Practical Guide To The Analysis...

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Genome Informatics 2010

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Provides an introductory overview of bioinformatics concepts and techniques.

GENOME INFORMATICS 2010: GENOME INFORMATICS SERIES...

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Bioinformatics and Functional Genomics

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Provides an introduction to bioinformatics and functional genomics.

Bioinformatics and Functional Genomics

Bioinformatics and Functional Genomics

Bioinformatics and Functional Genomics

Bioinformatics and Functional Genomics

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Programming for Computations - Python

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Provides a foundational introduction to Python programming and scientific computing.

Programming for Computations - Python: A Gentle...

Programming for Computations - Python: A Gentle...

Programming for Computations - Python

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Python for Data Analysis

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Provides a practical introduction to Python for data analysis and data manipulation.

Python for Data Analysis: Data Wrangling with...

Python for Data Analysis

Python for Data Analysis: Data Wrangling with...

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Provides a comprehensive overview of deep learning.

Deep Learning (Adaptive Computation and Machine...

Deep Learning (Adaptive Computation and Machine...

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Introduction to Algorithms, fourth edition

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This classic textbook provides a comprehensive overview of algorithms and data structures.

Introduction to Algorithms, fourth edition

Introduction to Algorithms, fourth edition

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Data Structures and Algorithms in Java

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This textbook provides a practical introduction to data structures and algorithms using Java.

Data Structures and Algorithms in Java

Data Structures and Algorithms in Java, 6th Edition

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Cover image

An Introduction to Bioinformatics Algorithms

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This introductory textbook provides a broad overview of computational molecular biology.

An Introduction to Bioinformatics Algorithms...

An Introduction to Bioinformatics Algorithms...

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Via

Coursera

Institution

Johns Hopkins University

Instructors

Ben Langmead, PhD

Jacob Pritt

Language

English

Transcripts

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Algorithms for DNA Sequencing belongs to the following collections:

Traffic lights

Read about what's good

what should give you pause

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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