Learner Reviews & Feedback for Introduction to Systems Biology by Icahn School of Medicine at Mount Sinai

Although I am thankful to the Icahn School of Medicine at Mount Sinai, Ravi Iyengar & colleagues and especially Coursera for providing the such courses online,

I have to say after taking this course that I did not find this helpful and would not really recommend it to anyone. The course is sort of a bird's eye view of the field of systems biology such that a beginner would not understand much of anything and an experienced researcher would also not really benefit from it either. In my view the course is sort of a "Review of certain handpicked literature" and it does not Explain well the basic concepts of system biology.

Tests do not reflect course information. Even if the title is "introduction" it asumes the user is familiar with a lot of topics. It is probably good for people that just need a reminder of something that they studied previousely.

They teach basic theory and then require the student to know much more on exams. Maybe this course should be done last in the specialization. (I'm hoping the others are better)

The lecture quality should be dramatically improved. Even at 2x speed, I feel Iyengar should further practice is presentation and redo the videos. In the conclusion, Iyengar states that no textbooks are available for the field because it is "new", but an Amazon search shows several seem to exist, and many of the studies referenced in this course are years old, even more than a decade in some cases... so I think better materials for more organized slides must exist. I've taken more than 5 coursera classes, and this has been my least satisfying. ... I do appreciate the introduction this provided, for free, and plan to keep learning in this space, though not in this course sequence.

Having completed somewhere in the region of 70 online courses I can say with complete honesty that "Introduction to Systems Biology" is the worst online course I have ever taken. The videos are a rambling sprawl with little coherence and are in need of serious editing. The amount of prior knowledge assumed is absurd for a course of this scope - and comments in the discussion forums seems to indicate that many others feel the same. In over 4 years since the course first started, there has not been a single post by the instructor and the lecture notes are as equally muddled as the lecture viedos. In all honesty, a prospective student would be better off buying one of the many excellent monographs on Systems Biology and taking a random page at KEGG and studying that. Frustrating and did not in any way meet my objective of gaining a good grounding in Systems Biology.

It's a challenging subject. Don't expect to walk away from the course with a complete grasp of systems biology. However, this course is a fantastic place to start.

Nice course, a little boring at the beginning with so much data about cell signaling, (kinases names, and specific routes).

This is a good course, overall - it starts off with a lot of technical detail about network, but I honestly encourage anyone to keep going with it as the second half of the course is full of really interesting material on signalling networks and modelling, and having finished it, I certainly feel much more informed. However, the assessments can be tricky - they often require rote learning of specific detail from the lectures (often, detail which isn't highlighted a particularly important). They also occasionally involve difficult to understand questions, and several questions have had spelling or grammatical errors.

However, overall, I'd recommend this if you have previous undergraduate education in molecular biology, and a general understanding of how cell biological systems work.

This course is difficult. Often very difficult. Sometimes extremely difficult. However, the assessments are reasonably accessible for someone who is not highly experienced in the relevant fields (i.e molecular biology, biochemistry or mathematical modelling). I enjoyed the course tremendously. The content of the course was stellar, and delivered to me exactly what I was hoping for from this course. When I first began the course I was quite surprised at the level of detail (this is my first time using Coursera, and I had thought the course would be a lot more "fluffy" or "wishy-washy" than it was). The level of detail was paired (almost always) with a description by Ravi Iyengar which was simple and captured the main "take-home" points. This I imagine is only possible thanks to the eminence and experience of Dr Iyengar and the hard-work by the rest of the team behind the scenes. Many aspects can be a little daunting (I did not understand anything with great deepness, I often did not understand things very much, but I rarely did not understand things at all - thanks to the emphasis on take-home points). I think an essential course for anyone who wants a taste of all things systems and networks.

An excellent introduction to Systems Biology. I studied electrical engineering for undergrad and neglected to take more than the single biology course that was required, so I was a little unsure of how the course would go. There are actually many parallels with systems biology and engineering, so most of the material was intuitive or could be easily fitted with my previous knowledge. I had to spend additional time for nomenclature and rechecking exam questions to make sense of the answers, but the class is organized in a way that you can actually acquire the information you need to build a foundation and be able to consider what researchers from various backgrounds are concerned with.

I think the course's goal is to make the students familiar with the concepts and terms in system's biology. At first it made me think that the subjects are not as connected as they should be. To be honest, if someone asks me about what exactly I learned from this course, I don't have any answer. It's like I have learned some diffuse ideas and concepts and I can't put them all together. but what I am certain about, is that this course made me look at things differently. And that is indeed what every class and course should do isn't it?:)

A good introduction to this topic for sure. As others have said, this is perhaps more like an "advanced" course than intermediate (I already have a masters in biochemistry and a lot of programming experience) but for me it's perfect. He does talk slowly though so I've been increasing the play speed to 1.5x

An exceptional course for anyone interested in the area of bioinformatics, cell biology, biotechnology, etc. I think it is very valuable to have some background in molecular biology but if you are interested, do not doubt to take it.

The required readings are stellar. I didn't know all this stuff, and there's a real open-source philosophy. The bio stuff is challenging for an engineer like myself, but worth Googling and learning in the long run

Very nice course, would have liked more interactivity / problem solving type questions

The course material seems a little bit outdated, and could benefit from update.

The lecturer is bad at communicating , The material is hard to understand , and he skims through the contents , The Quizzes are not related to the materials sometimes

Solution : No doubt that the lecturer is a distinguished person , but this kind of material should be taught by a young faculty member that can communicate much better with the students , the current lecturer can supervise the material and answer questions in the discussion boards

Given the constraints of the MOOC format, Professor Iyengar and his lab did an excellent job of presenting an introduction to this complex and still-developing field.

Ultimately, systems biology is more something that you do than something that you know about just from reading about it, but a course like this can serve as a jumping-off point for finding particular areas that interest you enough that you will put in the time and work to gain hands-on experience.

A minor complaint: The last question on the last lesson quiz (not the final) is a broad philosophical question, and several of the answer choices are defensible. The supposedly correct answer choice is one of the less reasonable ones. I would go into further detail, but it may not be appropriate to give away the answer here.

I think this is specialization is greatly helpful for people who want to learn more in depth about the field. But Dr Ivengar’s lecture notes should be more organized, I got confused reading through the notes sometimes due to the constant typos. Other than that, it is awesome but the course is not for a beginner as it said on the website.

This is a great platform to learn such complex topics broken down into small segments which helps to absorb and apply the knowledge in our respected work fields.I am very optimistic to complete all 6 of the course and by then I will actually learn some valuable things which I can apply in my own field of work.

Excellent introductory course. Professor Ravi Iyengar is very clear and has a broad knowledge of Systems Biology. Indicated papers help to understand the topics and allow the student to have a good starting point in each topic. Thanks all the team for the excellent course.

This is a very complete introduction to Systems Biology, I felt that I aquire relevant knowledge to undertake further courses on the subjetct. Hoever, the learning curve could have been less steep in this introductory course.

Very useful course in order to learn the basics in systems biology. You only need some training in biology to understand the concepts but the course is easy to follow and very complete.

It's really a nice introduction of system biology. I have learned a lot of new ideas.

Professor Iyengar is quite interesting! Still I hope more mathematical details can be included!

Great course! It explains very generally but clearly all different aspects involved in Systems Biology. The material used is good and so are the articles used for learning.

Great foundational material and insights from Prof. Iyengar that supports the 'disruptive' trends underway at the intersection of Computational Biology and Medicine.