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返回到 系统生物学中的网络分析

學生對 西奈山伊坎医学院 提供的 系统生物学中的网络分析 的評價和反饋

186 個評分
29 條評論


An introduction to data integration and statistical methods used in contemporary Systems Biology, Bioinformatics and Systems Pharmacology research. The course covers methods to process raw data from genome-wide mRNA expression studies (microarrays and RNA-seq) including data normalization, differential expression, clustering, enrichment analysis and network construction. The course contains practical tutorials for using tools and setting up pipelines, but it also covers the mathematics behind the methods applied within the tools. The course is mostly appropriate for beginning graduate students and advanced undergraduates majoring in fields such as biology, math, physics, chemistry, computer science, biomedical and electrical engineering. The course should be useful for researchers who encounter large datasets in their own research. The course presents software tools developed by the Ma’ayan Laboratory ( from the Icahn School of Medicine at Mount Sinai, but also other freely available data analysis and visualization tools. The ultimate aim of the course is to enable participants to utilize the methods presented in this course for analyzing their own data for their own projects. For those participants that do not work in the field, the course introduces the current research challenges faced in the field of computational systems biology....




It was a nice course with great information and resources for new people working or willing to work on bioinformatics



Excellent course to get deep into the data analysis of system biology experimentation.


1 - 系统生物学中的网络分析 的 25 個評論(共 29 個)

創建者 Erick C O


From the Systems Biology specialization courses, this is the one from where I have learned the most, in some way the reason is because I didn't know most of Network Analysis, but now I feel familiarized with it. I consider this is one of the most extended courses, and could be improved in the practice evaluation with more exercises.

創建者 Yalda Y


The content of each week was good (except for the RNA-seq lectures which I had no clue what the instructor was talking about!) but I think there was no integration between them and it was hard to connect everything in my brain. Also, lots of lectures were about how to analyze a list of differentially expressed genes but no one ever explained how to identify differentially expressed genes! which is why I'm stuck in the first step of my project.

Although I wasn't very satisfied by all the lecturers, I think Neil Clarke did a great job at explaining how some methods work.

Overall, I don't feel like I've learned network analysis in systems biology. Don't expect this course to make you an expert in the field.

創建者 Felix E R P


Excellent course to get deep into the data analysis of system biology experimentation.



Its really a very interesting course ,and very informative

創建者 DBSun


demanding and interesting , like it ~

創建者 Arif R


It's a comprehensive course, very resoureful. The course needs few update in terms of softwares/tools mentioned. Some of the lectures are hard to follow, especially if you are coming from non-bioinformatics background. Overall, an excellent course.

創建者 Carlos A F


Well elaborated and that brings an overview of bioinformatics and systems biology. The knowledge acquired is already being very useful and has helped me a lot in my investigations. My sincere thanks to Dr. Avi Ma'ayan, students and researchers for preparing this course.

創建者 Mimi D


I​ have learned alot from this course. This course really helped me to gained more knowledge. Thanks again. Love to see, new advanced course in Bioinformatics (personalised medicine) area. Please put more advanced course.

創建者 Esteban C


It was a nice course with great information and resources for new people working or willing to work on bioinformatics

創建者 Sandeep K


nice and very informative course

創建者 wiky


my favorite and the best course

創建者 Hamsini N


Very informative course.

創建者 Salvatore M


Thanks - excellent!

創建者 julio c r m


Excellent course .

創建者 Kirk G


Very good course

創建者 Mac D G



創建者 Alejandra R O



創建者 Doreen B


Very good course. Subjects are explained very well. Only downside is that it oscillates between these explanations to very dry demonstrations of specific tools. That is not to say they are not demonstrated well and thoroughly, but I prefer the theoretical background. Also, it's a shame that not all of the sites are completely functions - I was particularity disappointing by not being able to log on to the crowdsourcing site.

創建者 Adam H


A lot of useful information but the tests are very annoying. E.g. why should I know what javascript library is used to plot bar graphs in Enrichr or what is the meaning of a certain argument for a tool I didn't use. The section on processing sequencing data but also other could use more on-hands approach. Still, although sometimes a bit boring, I learned a lot.

創建者 Páidí C


The course material was great, and covered many interesting topics. But I found many of the problems didn't really test your understanding of the material, just whether you remembered some fact from the lectures.

創建者 Pooja R


Various analytical approaches for network analysis are very well explained. Also, have explained the working of different bioinformatics or network-based tools and software.

創建者 Dmitry B


It was a good review of various tools, but maybe it was to many tools. I think it would be nice to show a smaller number of tools, but make more reproducible showcases

創建者 Alessandro F


Exciting course. I think some contents should be updated but in general an exhaustive overview.

創建者 Alok S


The content of the class was interesting. However many of the resources described do not work properly. Perhaps a greater focus on offline techniques would be better if the Mayaan lab cannot invest the resources to maintain a bunch of servers.

創建者 Verena N


more explanation and practical examples during the course would have been helpful

good to get a rough overview of principles and tools

a lot of info was to learn by heart (and not to understand)