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Algorithms for DNA Sequencing

Genomic Data Science,

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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Rating 4.7 based on 132 ratings
Length 5 weeks
Starts Jun 26 (49 weeks ago)
Cost $49
From Johns Hopkins University via Coursera
Instructors Ben Langmead, PhD, Jacob Pritt
Download Videos On all desktop and mobile devices
Language English
Subjects Programming Data Science
Tags Computer Science Data Science Data Analysis Algorithms

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What people are saying

dna sequencing

For a course with a duration of just 4 weeks it covers an amazing amount of required DNA sequencing background material and algorithms.

Helpful material for DNA Sequencing and number crunching.Well taught, I suggest a background in Python to make things more enjoyable.

This course provided me a very quick overview of all the core concepts pertaining to DNA sequencing.

It delivers what it promises successfully and help understand the problem of DNA sequencing.

I suggest getting rid of your intro material and go just a little farther in depth.Thanks, MC It's a little bit hard for the fresh guys I really appreciate how much effort the authors have put into the course 'Algorithsms for DNA sequencing'.

Thanks a ton :) This course was very helpful at building a perspective of how useful algorithms are in DNA Sequencing!

This is a good (albeit short) introduction to algorithms for DNA sequencing.

I learned so much about algorithm in DNA sequencing.

Very good course on DNA Sequencing.

Recommend to anyone who want to learn more On Algorithms for DNA Sequencing!

A complete approach about algorithms in treatment of Massive DNA Sequencing Data.

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very good

Very good lectures.

Very good course I enjoyed it a lot.

Very good job in how the topic is explained to the students with writing code dynamically.

very informative perfect !!! Very good course!

Very good!

Thank you This was a very good course!

Very good introduction to python programming in biology.

very good and very helpful Amazing experience so far Great course.

Ben is a very good teacher.

Very good teaching material, video lectures and practical sessions.

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genomic data science

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.

The assignments took me a lot of time because my only programming background is the 'Python for Genomic Data Science' course.

However, for somebody that only has the programming knowledge from Course 3 of the Genomic Data Science Specialization (Python for Genomic Data Science), that course, I believe, is too light for the new Python concepts taught in this course.

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ben langmead

It was only after completing the course that I realised that the course instructor, Ben Langmead, is actually the first author of the bowtie paper which is one of the most commonly used programs for DNA mapping.

Dr. Ben Langmead, along with lecturer Jacob Pritt, has done a magnificent job at making this course engaging, progressive and fun.

Ben Langmead explains concepts very clearly and has clean, well-structured presentations.

Thanks to wonderful instructors: Ben Langmead, PhD and Jacob Pritt.

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other courses

The algorithms employed are much better explained than in some other bioinformatics courses on Coursera that deal with some similar topic (UCSD Specialisation, etc) as the course specifically deals with the algorithms rather than teaching bioinformatics in general (though I find the other courses quite good too).

I have taken six other courses in this JHU Genomics series on Coursera and many others in Data Science @ JHU, Cybersecurity @ the U of Maryland etc on Coursera.

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programming language

The Practical courses are extremely useful, and help a great deal to understand how the algorithms described during the lectures can be easily applied in an accessible programming language.

The course also provided an excuse to learn some of the Python programming language, which I encounter from time to time in my current career.

Any other programming language would probably be fine but the language of choice for the course is Python.

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homework assignments

Also, the "hints" to accomplish the homework assignments were definitely not well explained.

Some of the homework assignments were kind of hard though (and no help in the discussion forums).

The homework assignments are challenging, but created in such a way that the difficulty lies more in grappling with the concepts themselves, and less with debugging python code or whatever.

The homework assignments are challenging but not frustratingly so.

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for people

Recommended for people of all backgrounds who want to learn how sequencing works.

It is a very helpful course, explains domain terms and constructs a background for people that have no background in bioinformatics.

Lectures are very well prepared, practicals provide step-by-step explanations of the scripts (which is especially useful for people with little coding experience) and homeworks are well thought through, so that they force students to use the knowledge gained in the module.

Content is very well structured, lectures are very good and interesting, with additional "optional" lectures which provide extra knowledge for people who are interested.

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well explained

The lecture material is extremely well explained and accessible both to students with a computational background and to biologists.

well explained This is hands-down the best course in this specialization.

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commonly used

This course deals with the algorithms employed by mapping and genome assembly programs commonly used.

Very well prepared, from basics up to all commonly used techniques in bioinformatics.

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An overview of related careers and their average salaries in the US. Bars indicate income percentile.

Research Technologist, Laboratory Automation & Next-Generation Sequencing $37k

DNA Lab technician $45k

DNA Technician 1 $60k

Senior DNA Analyst $67k

Warehouse Sequencing Lead $70k

DNA Sequencer Manager $78k

Senior DNA Loan Analyst $92k

DNA Lab technician 2 $93k

DNA Sequencer 1 $95k

DNA/RNA Researcher $109k

DNA Lab technician Lead $116k

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Rating 4.7 based on 132 ratings
Length 5 weeks
Starts Jun 26 (49 weeks ago)
Cost $49
From Johns Hopkins University via Coursera
Instructors Ben Langmead, PhD, Jacob Pritt
Download Videos On all desktop and mobile devices
Language English
Subjects Programming Data Science
Tags Computer Science Data Science Data Analysis Algorithms

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