You may have heard a lot about genome sequencing and its potential to usher in an era of personalized medicine, but what does it mean to sequence a genome? Biologists still cannot read the nucleotides of an entire genome as you would read a book from beginning to end. However, they can read short pieces of DNA. In this course, we will see how graph theory can be used to assemble genomes from these short pieces. We will further learn about brute force algorithms and apply them to sequencing mini-proteins called antibiotics. In the first half of the course, we will see that biologists cannot read the 3 billion nucleotides of a human genome as you would read a book from beginning to end. However, they can read shorter fragments of DNA. In this course, we will see how graph theory can be used to assemble genomes from these short pieces in what amounts to the largest jigsaw puzzle ever put together. In the second half of the course, we will discuss antibiotics, a topic of great relevance as antimicrobial-resistant bacteria like MRSA are on the rise. You know antibiotics as drugs, but on the molecular level they are short mini-proteins that have been engineered by bacteria to kill their enemies. Determining the sequence of amino acids making up one of these antibiotics is an important research problem, and one that is similar to that of sequencing a genome by assembling tiny fragments of DNA. We will see how brute force algorithms that try every possible solution are able to identify naturally occurring antibiotics so that they can be synthesized in a lab. Finally, you will learn how to apply popular bioinformatics software tools to sequence the genome of a deadly Staphylococcus bacterium that has acquired antibiotics resistance.
QL
It would be great if all the slides for every week could be shared. The Bioinformatics II is much harder than the last level. They've made it easy to learn.
ZX
In depth and comprehensive coverage of the topics in genetic data analysis.
BN
Really enjoyed the course. Dropped from five to four stars because the final challenge introduced several new concepts rather than integrating concepts taught throughout the class.
DB
This is a well organized course with excellent interactive programming exercises that help with learning the concepts.
EH
Excellent! I have learned a lot. Pavel Pevzner is a boss of bioinformatics.
CG
Very good course. The course staff needs to take a look at some pseudo codes and stepik assessments because they are kinda heavy to process. Besides that, great info and development.
FR
It's really a great course. A must for everyone working with bioinformatic tools in order to understand some basics and limitations that ultimately leads to biological conclussions
SC
Another excellent course. Great to be able to start from a basic idea and keep expanding it until we look back and see we've learnt how to solve quite a complex problem!
CC
There is no debug dataset like the previous course, which means you will get stuck longer.
RP
This one is great introductory course for physicist like who knows the computing but lacks biological background.
CO
The course outline is very informative and the weekly quizes very challenging. I recommend this course to everyone who seeks to have a good background in Bioinformatics.
CF
The exercises were challenging. But thanks to the community in Stepik, I can understand more details for the genome sequencing algorithms.
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Course is abandoned, no support on forums, waiting for weeks for peer-reviews, images don't load in the interactive text and quizzes, links in assignments are broken. Coursera should refund me for this joke.
lectures is very informative but the quizzes assignments are too difficult ans most of the question in quiz wasn't studies in lectures
It's really a great course. A must for everyone working with bioinformatic tools in order to understand some basics and limitations that ultimately leads to biological conclussions
There is a lot to learn in this course, and a lot of complex coding needed if you complete the coding exercises. I am not sure how well anyone would get on without a solid coding background. Taken separately, there are the course videos, and the Stepik based coding activities. The videos are very good, and I think are a must for getting an overview of the course teaching. The stepik coding activiites have taught material which re-covers the videos in text for, BUT there is something of a disconnect between the two - almost like someone updated one but not the other? Or that the two production teams didnt talk? So be prepared to work your way through some confusion in that area. There are also considerable variances ad inconsistancis as you go through Skepic week by week - again subtle chnages that are not always flagged - again sugesting partial either poor proof reading or un synchronised changes over time.
In a less complex course (both biologically and computationally) one would quickly resolve these - but when the core material itself is challenging this become an unnecessary frustration.
There is a studnt discussion forum for each activity, and this can be helpful - but one needs to sort the wha=eat from the chaff - some is helpful and correct, other contributions plain wrong! Although there is a lot of this contribution, it is now quite dated - so dont expect a prompt response to any questions you raise.
Finally a major area of frustration for me was debugging my code. Often a pseudo-code algortihm is provided, and test data, but for the most complex coding assignments simply being told that the answer is wrong, with no indication as to why, is a problem - particulalrly when it appears that the grader is very sensitive to things like spaces and new lines in your response!
Bottom line - the video teaching is interesting and informative, the coding challenges not for the faint hearted, be preapred to work through ambibuous and inconsistant instructions - and probably best to read all the discussion forums for the known 'gotchas' before you start codning and testing the programming activities.
Long waits for peer review....ruins what is a good course.
Spend a huge amount of time because of mistakes in tasks!
These courses are consistently excellent. The are possiblly the best entry point for someone wishing to have a go at bioinformatics.
The course needs updates EXAMPLE: The version 3.0 for spades doesn't give the statistics and if you do a new version it doesn't give you the same data. I think this happened to other students, but we used Quast that it was later described in the instructions, but if it wasn't because someone suggested it in the discussion I would have follow the same path of using a new version that would have given me wrong data.
Thank you so much, This course has been helping me a lot.
CHEERS!!!
A really rewarding course! Definitely shifted up a gear compared to the preceding course, so I recommend doing this in the prescribed order.
The course is great, but be prepared to spend 20-30 hours a week on it...
While the skills this course teaches are great, the course feels abandoned, it takes forever to get your assignment reviewed, some of the code assignments are buggy and there is very little explanation as the course progresses
As with the first course, much of the writing of this course is in need of improvement. Poorly written course material leads to wasted time in trying to decipher what the instructor means.
The course, although good, seems to be abandoned as there were no responses from teaching staff for months, and several students were stuck on final assignment for weeks.
Great Materials but bad support
The UCSD affiliation is really the only reason to do this course. It is so much harder than it needs to be.
Chapter 3 was absolutely wonderful. I am a math guy, not a biologist, so of course I loved this. Really stunned by all the complications that arise in applying the math to real biology. In Chapter 4 I thought the discussion of the mass spectrometer was really confusing. Some very basic ideas were never made clear. The mass spectrometer is a "breaker", not a "blender", so you don't get all possible sub-strings. The video lectures by the young professor finally helped me to understand what was going on. I have the book, so the online shortened version is not very helpful, but the videos are generally very good. The navigation through the course, and the separate hacker track, gets confusing some times. I think I have to click through the hacker track, but I'm not sure. I am very comfortable with programming, but don't have the time to do the hacker track. It looks VERY time consuming.
I learned a lot on this course. Sequencing, sequencing antibiotics. Ilumina sequencing using BaseSpace. I attended an Ilumina seminar in person ( that I found on the website and by serendipity was coming to my city) and understood everything, because the experience with this course. I wish you can connect the sections with relevant papers (Pavel have so many that is hard to choose one).
The course is absolutely fantastic. Concepts are introduced gradually, and you get away with solid fundamentals of genome sequences.
Beware however that the course is not actively maintained any longer and has few participants. It may be that your final assessment will take a bit to be graded by the peers and the forums are not super active.
If you liked first course, you must take second course too, one of the most enjoyable and challenging courses available. It's great not only for bioinformaticians, but for people who are interested in algorithms and their application.
Excellent course. I didn't have the time to follow the honor's track, but I've done it for other instances of the specialization and I can say that the interaction with Stepic works perfectly. Way to go, thank you!