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Algorithms for DNA Sequencing, Johns Hopkins University

4.8
397 Bewertungen
90 Bewertungen

Über diesen Kurs

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....

Top-Bewertungen

von VK

Aug 08, 2017

This course provided me a very quick overview of all the core concepts pertaining to DNA sequencing. It is very well organized, crystal clear demonstration of concepts and I really enjoyed the course.

von AZ

Mar 11, 2016

Awesome, you will learn a lot about how DNA assemblers work, but very challenging and time demand in, especially if your background is in life science and not computer science.

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88 Bewertungen

von

May 19, 2019

This was an outstanding class. Thank you very much.

von Xiaoou Dong

May 07, 2019

Very clear presentation. Good analogies used to help with understanding abstract concepts. Both instructors are excellent teachers.

von Carlos Martinez

Mar 22, 2019

Great material, nicely presented.

von Yafremau Nicholas

Jan 11, 2019

This is one of the best courses I've seen so far, that explains and showcases main principles, fundamentals of genomics, algorithms. Lectures are very informative and use metaphors for person to understand complex tasks in simple manner. I loved practicals as you could go along with the lecture in parallel, seeing how such algorithms were made and what steps to take while doing so. 5/5

von Stephanie Tara Eristoff

Jan 06, 2019

This course was a really awesome course for anyone that has a light background in Python and wants to look more into bioinformatics. The instructors were very passionate and clear, and there was a good balance between learning about biology and the programming aspect. 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. I believe that before taking this course, you may need more background knowledge for Python. However, this is still a stellar course that I greatly enjoyed, with the homework and assignments being appropriately challenging.

von Geoffrey Knox

Nov 17, 2018

I was completely new to Python when I started this course - and the good news is I learned enough to complete! (Yay!)

I suspect I'd have given the course 5 stars had I started with slightly more Python knowledge.

Still, the feeling of having got through is sweet all the same!!

von Cheng Jie

Nov 12, 2018

The course is very helpful to me,especially the code that the professor assistants wrote in the class. There are some algorithms have mentioned and completed ,but I think if the class talked about the software like BWA, BFAST and other DNA sequence or De novo assembly software, it will be more perfect and helpful. Finally ,thank you for your work

von Omar Elgazzar

Oct 19, 2018

I loved this course a lot. It's well organized. The lectures are clear. And the practicals are highly useful. Also, the assignments are helpful.

von Yueqi Chen

Sep 24, 2018

This is a super nice course.

von Joanna Wenda

Aug 31, 2018

This is an excellent course. 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. Some of the homeworks are challenging, but all the information needed to do the exercises is provided in lectures and practicals. All the notebooks containing scripts are provided, which makes it easy to take notes and better understand the scripts by running some examples. The way the concepts are explained in the lectures (the computational problem is described in details and then the ways of dealing with it are carefully explained in order of increasing complexity) provides insight into not only how these algorithms work but also why (what is the purpose/cause/reason behind these solutions). I can imagine how much work and thought went into preparation of these lectures and I honestly admire the teachers for their efforts. Taking this course was a great experience: I learned a lot and enjoyed it a lot. A big thank you! Please, keep up the good work.