Bioinformatics Algorithms (Part 1)

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9/10 stars
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Coursera online courses
Coursera's online classes are designed to help students achieve mastery over course material. Some of the best professors in the world - like neurobiology professor and author Peggy Mason from the University of Chicago, and computer science professor and Folding@Home director Vijay Pande - will supplement your knowledge through video lectures. They will also provide challenging assessments, interactive exercises during each lesson, and the opportunity to use a mobile app to keep up with yo...
Coursera's online classes are designed to help students achieve mastery over course material. Some of the best professors in the world - like neurobiology professor and author Peggy Mason from the University of Chicago, and computer science professor and Folding@Home director Vijay Pande - will supplement your knowledge through video lectures. They will also provide challenging assessments, interactive exercises during each lesson, and the opportunity to use a mobile app to keep up with your coursework. Coursera also partners with the US State Department to create “learning hubs” around the world. Students can get internet access, take courses, and participate in weekly in-person study groups to make learning even more collaborative. Begin your journey into the mysteries of the human brain by taking courses in neuroscience. Learn how to navigate the data infrastructures that multinational corporations use when you discover the world of data analysis. Follow one of Coursera’s “Skill Tracks”. Or try any one of its more than 560 available courses to help you achieve your academic and professional goals.

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4629 reviews

Course Description

The sequencing of the human genome fueled a computational revolution in biology. As a result, modern biology produces as many new algorithms as any other fundamental realm of science.  Accordingly, the newly formed links between computer science and biology affect the way we teach applied algorithms to computer scientists.

This course has now been split into three smaller pieces:

  • Finding Hidden Messages in DNA: This course begins a series of classes illustrating the power of computing in modern biology. Please join us on the frontier of bioinformatics to look for hidden messages in DNA without ever needing to put on a lab coat. After warming up our algorithmic muscles, we will learn how randomized algorithms can be used to solve problems in bioinformatics.
  • Assembling Genomes and Sequencing Antibiotics: Biologists still cannot read the nucleotides of an entire genome or the amino acids of an antib...

The sequencing of the human genome fueled a computational revolution in biology. As a result, modern biology produces as many new algorithms as any other fundamental realm of science.  Accordingly, the newly formed links between computer science and biology affect the way we teach applied algorithms to computer scientists.

This course has now been split into three smaller pieces:

  • Finding Hidden Messages in DNA: This course begins a series of classes illustrating the power of computing in modern biology. Please join us on the frontier of bioinformatics to look for hidden messages in DNA without ever needing to put on a lab coat. After warming up our algorithmic muscles, we will learn how randomized algorithms can be used to solve problems in bioinformatics.
  • Assembling Genomes and Sequencing Antibiotics: Biologists still cannot read the nucleotides of an entire genome or the amino acids of an antibiotic as you would read a book from beginning to end. However, they can read short pieces of DNA and weigh small antibiotic fragments. In this course, we will see how graph theory and brute force algorithms can be used to reconstruct genomes and antibiotics.
  • Comparing Genes, Proteins, and Genomes: After sequencing genomes, we would like to compare them. We will see that dynamic programming is a powerful algorithmic tool when we compare two genes or two proteins. When we "zoom out" to compare entire genomes, we will employ combinatorial algorithms.

Each course parallels two chapters from a textbook covering a single biological question and slowly builds the algorithmic knowledge required to address this challenge.  Along the way, coding challenges and exercises (many of which ask you to apply your skills to real genetic data) will be directly integrated into the text at the exact moment they are needed.

Reviews 9/10 stars
32 Reviews for Bioinformatics Algorithms (Part 1)

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10/10 starsCompleted
2 years, 8 months ago
This course has the most enthusiastic, offbeat and committed instructors I've ever met. The duo takes the learners on amazing trip into the fascinating world of bioinformatics, using examples and analogies from everyday life and popculture as a background. Good work, guys! I'm going to take another courses with you!
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8/10 starsCompleted
2 years, 12 months ago
The course content is pretty good, lot of CS and algorithms. There were a few place where I wish the explanations of the algorithm were more clear. The instructors were very good but wish they did like a 1/2 hour of Q&A every week or something. I did find the Coursera interface to be non-intuitive at first but it was OK afterwards. The instructions about grading policies left a lot to be desired. There was a quiz where they suddenly changed the grading policy from 3 attempts to only the first attempt will count and never made it clear while I was doing attempt 2. Consequtively, I thought I had passed the course when in fact I was short by a few points. Coupled with the fact that Coursera Customer "service" is non-existent or not helpful, made for a somewhat frustrating experience in the end. All in all, was a pretty good course but can't get close to taking the same course in the university setting.
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8/10 starsCompleted
3 years ago
It's the third time I signed up for this course, because I never had enough time to work on it... The content is more programming than biology and some biological concepts are not explained in great detail. Since I had no prior knowledge of biology (other than high-school biology) sometimes I felt the need to search additional explanation online. I think I'll sign up for biology or genetics 101 to understand these concepts better. The programming tasks are not too complex, but not really easy either. I had trouble finding the issues I had in the last programming task and never managed to fix it. Maybe additional unit tests or debug datasets would be useful. Overall, I liked the course and I will recommend to anyone who is interested in Bioinformatics.
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6/10 starsCompleted
3 years ago
The course content was excellent--computer algorithms to analyze DNA sequence data. The textbook (I bought the hard copy) was excellent--the algorithms were clearly explained and there was additional material covering the biology and mathematics of the topic. The instructors were clear, friendly and helpful. They appeared in the class videos and on the discussion boards. The TA was also very helpful, friendly and candid. There were a number of providers, coursera and the group which supported the electronic textbook. There were a number of bugs which were usually, but not always fixed.
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10/10 starsCompleted
3 years, 1 month ago
As a biochemist, I would not take the course to learn biochemistry/molecular biology. However, it delivers precisely what it promises-an in-depth understanding of how algorithms function. The instructors build up the depth of understanding in steps, through the use of examples and pseudocode. I have tried to read treatises on the very same algorithms presented in this course but would never have connected the dots on my own. After coding all these algorithms myself, I have an understanding of how they work on a level I could never have achieved by any other means. I would like the algorithm that drives MEME (Expectation Maximization). As the bioinformatics challenge demonstrates, it far outperforms the others studied in motif identification. The professors do check the discussion forums and are responsive on some key issues. However, there are areas in which many students have expressed difficulties (e.g. Greedy algorithm) and ... As a biochemist, I would not take the course to learn biochemistry/molecular biology. However, it delivers precisely what it promises-an in-depth understanding of how algorithms function. The instructors build up the depth of understanding in steps, through the use of examples and pseudocode. I have tried to read treatises on the very same algorithms presented in this course but would never have connected the dots on my own. After coding all these algorithms myself, I have an understanding of how they work on a level I could never have achieved by any other means. I would like the algorithm that drives MEME (Expectation Maximization). As the bioinformatics challenge demonstrates, it far outperforms the others studied in motif identification. The professors do check the discussion forums and are responsive on some key issues. However, there are areas in which many students have expressed difficulties (e.g. Greedy algorithm) and more input and guidance would be preferred. It is this expertise that we need them for as they understand these concepts inside and out-likely trivial. Great course and I will certainly complete the entire series.
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Manar Mohamed Rashad profile image
Manar Mohamed Rashad profile image
8/10 stars
  • 1 review
  • 0 completed
3 years, 2 months ago
at the beginning of this course, I think that I won't benefit from it but after that I really happy to take it and benefit from great knowledge thanks a lot for this experience :)
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Benny Franco Dennis profile image
Benny Franco Dennis profile image
10/10 starsCompleted
  • 1 review
  • 1 completed
3 years, 2 months ago
This Was an amazing course, I liked the content because was easy for understand, the instructors was pending about every incidence, definitely I recommend this course.
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8/10 starsCompleted
3 years, 6 months ago
It was a rather pleasant experience. I enjoyed coding a lot, the only downside it's that it starts easy (too guided coding) and ends up rough (explanations are poor and ambiguous). Anyway, the staff was always helping at the forums so you could finish your assignments.
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Артём Ильин profile image
Артём Ильин profile image
10/10 starsCompleted
  • 1 review
  • 1 completed
3 years, 6 months ago
Great course! It implements a very sophisticated platform - Stepic, which in my opinion is more enjoyable, than Coursera. Also the course is very stimulating and you can't complete it without actually learning to build some bioinf tools
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10/10 starsCompleted
  • 1 review
  • 1 completed
3 years, 6 months ago
A very good course. It's a little difficult if you don't have a CS background, as the informatics part is a lot harder and counts more than the biology part. For me, it has been a great way to learn new things that I did not know and specially to discover a new exciting field.
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10/10 starsCompleted
3 years, 6 months ago
an excellent and a well organized course. I enjoyed being in the class and the excellent bridge between biology and informatics was explained really well
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Carlos P. Roca profile image
Carlos P. Roca profile image
10/10 starsCompleted
  • 6 reviews
  • 6 completed
3 years, 9 months ago
This is an extraordinary course. It requires commitment and a fair amount of time, but this is what implies the approach of guiding students step-by-step to implement themselves the algorithms. In my opinion, this is the best (and maybe, the only) way to fully understand how algorithms work. There are also explanations about the underlying biology and how it affects the design of the algorithms. I also liked the idea of presenting an analytical need from some biological data as a problem that you address progressively, trying and improving different ideas until you find a way that works. This gives students a glimpse of how research on algorithms is done and how new methods are invented.
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10/10 starsCompleted
3 years, 9 months ago
An excellent blend of genetics and comp sci. This is exactly what I was after as a CS person. I'd be interested to know what a life sciences person thought of the material.
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Erika Álvarez profile image
Erika Álvarez profile image
10/10 starsCompleted
  • 1 review
  • 1 completed
3 years, 9 months ago
I wanted to see what the bioinformaticians have to deal with, and I learnt it in a funny, entertained way. Some times the problems are easy, but there are also some real code challenges, and for these you need to have extra time, so, if you work or study, try not to take other on-line courses. The methods needed in bioinformatics are great, then, the course is not just entertaining because of the codes, but also because the math involved is interesting. This is the best course I have found in Coursera, followed by "An introduction to interactive programming in Python", I highly recommend it, you will love it.
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10/10 starsCompleted
3 years, 9 months ago
I am currently doing a PhD in bioinformatics. I have taken several courses from a wide range of subjects, but this is, hands down, the best course I have ever taken. This course will give you a thorough understanding of algorithmic approaches to common problems in bioinformatics. It is a tough course, which will definitely test your abilities in logical thinking and programming. I would recommend that you have a good background in the programming language of your choice. I used python for all the exercises, which worked wonderfully, but I imagine it would be hard if I did not have any prior experience. With that said, if your programming skills are moderate, as mine was, you will undoubtedly learn a lot while solving the various code challenges in this course. For me, the hardest part was not understanding the algorithms themselves (most challenges come with provided pseudocode), but getting my programs to run correctly and efficien... I am currently doing a PhD in bioinformatics. I have taken several courses from a wide range of subjects, but this is, hands down, the best course I have ever taken. This course will give you a thorough understanding of algorithmic approaches to common problems in bioinformatics. It is a tough course, which will definitely test your abilities in logical thinking and programming. I would recommend that you have a good background in the programming language of your choice. I used python for all the exercises, which worked wonderfully, but I imagine it would be hard if I did not have any prior experience. With that said, if your programming skills are moderate, as mine was, you will undoubtedly learn a lot while solving the various code challenges in this course. For me, the hardest part was not understanding the algorithms themselves (most challenges come with provided pseudocode), but getting my programs to run correctly and efficiently. The suggested 10 hours per week is an absolute minimum. This might be enough for people with a lot of coding experience, but I used 2-3 times as long for the hardest chapters. The material is beautifully and logically presented, with each chapter going having a logical build-up. The chapters start by introducing a computational problem, and then slowly build your understanding on algorithms that can be used to solve it. Examples and interesting anecdotes are provided as topping along the way. My only gripe is the rigidity of the automatic grader in some of the exercises. You may have a technically correct answer, but it will not always be accepted if, say, the formatting is slightly off or (in at least one exercise) if you have solved the problem in another way than originally intended.
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10/10 starsCompleted
3 years, 9 months ago
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Conrad Stack profile image
Conrad Stack profile image
8/10 starsCompleted
  • 1 review
  • 1 completed
3 years, 9 months ago
The course content is comprehensive, but with a limited scope. This give the course a manageable scope while still providing a solid foundation in Bioinformatics. The one issue I had with the class was input/output data formatting in the course exercises. The automated grader for these is too rigid and I feel like I spent too much time formatting relative to the time I spent working out an algorithm. Despite this, the coding challenges were indeed challenging, but balanced.
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Ken Sellers profile image
Ken Sellers profile image
10/10 starsCompleted
  • 1 review
  • 1 completed
3 years, 9 months ago
Of the half dozen or more MOOCs I've taken, this class is in the top two. MIT 7.00x, taught by Eric Lander, is the only one that is on the same level. This is the highest compliment that I can give; I loved 7.00x. The prerequisites I recommend are an introductory DNA class (MIT 7.00x or equivalent), some programming experience, and (optionally) some formal exposure to algorithms. I do not think someone whose lifetime programming experience consists of completing a single introductory Python class will do well, though it is possible. You are allowed to complete the assignments in the language of your choice; I chose C++. The material is presented as a collection of video lectures, and an "interactive text" that breaks the written material into many small, easy-to- digest pieces. I typically watched a video and then immediately dived into the corresponding text. On the rare occasion that I had trouble with the material, the d... Of the half dozen or more MOOCs I've taken, this class is in the top two. MIT 7.00x, taught by Eric Lander, is the only one that is on the same level. This is the highest compliment that I can give; I loved 7.00x. The prerequisites I recommend are an introductory DNA class (MIT 7.00x or equivalent), some programming experience, and (optionally) some formal exposure to algorithms. I do not think someone whose lifetime programming experience consists of completing a single introductory Python class will do well, though it is possible. You are allowed to complete the assignments in the language of your choice; I chose C++. The material is presented as a collection of video lectures, and an "interactive text" that breaks the written material into many small, easy-to- digest pieces. I typically watched a video and then immediately dived into the corresponding text. On the rare occasion that I had trouble with the material, the discussion forums were a good place to get help. You are graded on homework (programming assignments) and quizzes. The quizzes are easy if you read the material and do the assignments. The "heavy lifting" is the assignments, not so much due to their difficulty as to their quantity. There were 55 graded assignments, and at least a dozen optional assignments, some of which taught you how to approach the graded assignments. Each assignment asks you to perform some computational task on some data. You are provided with a tiny dataset which is useful for program development, and a practice dataset which is usually a good predictor of whether your program can handle the graded dataset. When you feel you are ready to be graded, you are given a unique dataset and 5 minutes to return the answer. If you fail to give the correct answer, you can try again, as many times as needed. If this sounds like a lot of work, it is! But don't be scared of it. This class reaffirmed for me the truth of the saying, "you get out of it what you put into it". I got a whole lot out of it.
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10/10 starsCompleted
3 years, 9 months ago
I enjoyed the course very very very much..it was like a beautiful thrilling dream.....first time I appreciated what scientist are doing ..I want to be part of it I wish I knew Python so that my progress would be faster (I think) but no harm I polished my skills in C#; I spent more than 7 hours every day of studying the course I tried certification process but the computer gave me hard time to understand my typing style...
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Robert Davis profile image
Robert Davis profile image
10/10 starsCompleted
  • 16 reviews
  • 16 completed
4 years, 5 months ago
This is a tough course. I would suggest you already have a good understanding of the python language before you start. I enjoyed this class and the easy- going nature of the instructor. I am looking forward to part 2, and will take part 1 again when it is available.
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Equanimous Creativity profile image
Equanimous Creativity profile image
10/10 starsCompleted
  • 33 reviews
  • 32 completed
4 years, 7 months ago
This is one of the best and most time consuming courses I have taken. At this courses there is programming assignment each week if you have no experience in programming take "Introduction to Systematic Program Design" before attempting this one. My only which was that biological part of the course was bigger.
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Alison Scott profile image
Alison Scott profile image
10/10 starsCompleted
  • 5 reviews
  • 5 completed
4 years, 9 months ago
A wonderful course, best for people with some previous programming and a little previous biology (I had MIT 6.00x and MIT 7.00x which was fine). The material is presented in two different ways; through face to face lectures, and through an online textbook (stepic.org) that presented the information step by step, inserting the coding exercises right into the text at the relevant point. I used mostly the textbook with only a little lectures; others did it the other way around. The entire grade is coding exercises. I took about ten hours a week on average, but a couple of the weeks were nearer 20 so you need to factor that in when considering doing this course (they doubled the length of the course part way through because it was obvious that people were struggling). Deadlines are reasonably long so you can pace this. Staff were responsive and the forums were helpful and constructive. We had some downtime on the grading server which was... A wonderful course, best for people with some previous programming and a little previous biology (I had MIT 6.00x and MIT 7.00x which was fine). The material is presented in two different ways; through face to face lectures, and through an online textbook (stepic.org) that presented the information step by step, inserting the coding exercises right into the text at the relevant point. I used mostly the textbook with only a little lectures; others did it the other way around. The entire grade is coding exercises. I took about ten hours a week on average, but a couple of the weeks were nearer 20 so you need to factor that in when considering doing this course (they doubled the length of the course part way through because it was obvious that people were struggling). Deadlines are reasonably long so you can pace this. Staff were responsive and the forums were helpful and constructive. We had some downtime on the grading server which was frustrating, but deadlines were extended. By the end I had learnt a ton about coding algorithms in Python and runtime, and quite a lot about how algorithms are used in bioinformatics. And I loved every minute of it, except for the times I couldn't get my code to run in less than five minutes (the grader timeout). I also loved the feeling that I was working with up to date science.
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10/10 starsCompleted
4 years, 9 months ago
Zero experience with biology, but lots with programming & algorithms. One of the best classes I've taken (I did CS at Stanford) The algorithms described here are beautiful. They are state of the art (some as young as 5 years old). They are expertly described. The course is hands on - you actually get to implement the algorithms. Overall, one of the most enlightening courses I've ever taken.
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10/10 starsCompleted
4 years, 9 months ago
The course is a nice review of many basic computer science algorithms as well as some advanced ones, and how they apply to solving actual real-world problems in genetics. Significant effort is required as there are up to 8 programming exercises per week (some of which might require several hours of implementing and debugging), but the reward is well worth it. The video lectures were not particularly useful to me, except for the week where the instructors tried to see how important the Stepic platform is, and removed all non-essential data from it. All other weeks were all completely covered on Stepic (course notes, information, algorithms, guidance), which I actually found more helpful than the video lectures. I did not check the other platform, Rosalind, since it was not mandatory (perhaps it should be in some way).
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10/10 starsCompleted
4 years, 9 months ago
Amazing course. It is quite demanding but you learn a lot. It deals with an advanced topic (bioinformatics) using a wonderful online book. It is an advanced course, some programming experience (10-12 weeks course) would be highly desirable. If you don't have it you'll have to learn it fast during the course.
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Guillermo Garcia profile image
Guillermo Garcia profile image
10/10 starsCompleted
  • 1 review
  • 1 completed
4 years, 9 months ago
Very well organized, very good material and CHALLENGING! I felt very satisfied when finishing the assignments.
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Rita Shnai profile image
Rita Shnai profile image
10/10 starsCompleted
  • 1 review
  • 1 completed
4 years, 9 months ago
The course is very interesting. It makes you think and incites further interest. I recommend it to any dev looking for better understanding of algorithm applications. I also recommend it to any bio interested in understanding of his/her data processing. I recommend it to anyone looking for widening his/her horizon. Please take into consideration that course will require a lot of work. It is not hard to understand, on the contrary, all material is well explained and easy to understand, but you need a lot of work for completing assignments.
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EunCheon Lim profile image
EunCheon Lim profile image
10/10 starsCompleted
  • 1 review
  • 1 completed
4 years, 9 months ago
I am currently performing researches in Max Planck Institute as a bioinformatics PhD student. I have almost-none background in biology but a very long-term experience in software engineering (more than 2 decades). This is one of the best courses that I've ever taken. Especially, this course provide a challenging but interesting exercises, assignments and detailed text as well as video lectures. The text and pseudo codes are sometimes unclear. Some assignment do not have sufficient amount of testing data sets and their expected output or the grader would not work as you expected. However, you could overcome such problems by taking a look at the discussion board.
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Arleigh Birchler profile image
Arleigh Birchler profile image
10/10 starsCompleted
  • 1 review
  • 1 completed
4 years, 9 months ago
I have a degree in Biology and have worked extensively in the computer profession and with algorithms. This course is very much hands-on. The lectures give some background, but most of the work is in the online course book and in designing algorithms and writing programs to solve bioinformatics problems. It is also a portal to several exciting crowd-sourcing projects working with professors from various institutions on bioinformatics problems.
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10/10 starsCompleted
4 years, 9 months ago
\- I study Biology and took an online course "Python for beginners", almost no other programming experience. \- The course difficulity was Medium-Hard for me, and VERY time consuming (since I had almost no computer science knowledge, debugging took ages). \- The online forum is really active and helpful! Many students and even the professors themselves write helpful comments all the time. \- You can definitely pass this course even without being a coding specialist, but it can make things very time consuming. \- I feel like I really learned a lot and I'm looking forward to part 2!
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