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Вернуться к Сетевой анализ в системной биологии

Отзывы учащихся о курсе Сетевой анализ в системной биологии от партнера Школа Медицины Икан на горе Синай

Оценки: 186

О курсе

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....

Лучшие рецензии


23 июля 2020 г.

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


2 июня 2016 г.

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

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1–25 из 29 отзывов о курсе Сетевой анализ в системной биологии

автор: Erick C O

10 мая 2016 г.

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.

автор: Yalda Y

26 апр. 2021 г.

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.

автор: Felix E R P

3 июня 2016 г.

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

автор: C.RAMYA

6 апр. 2016 г.

Its really a very interesting course ,and very informative

автор: DBSun

28 мар. 2016 г.

demanding and interesting , like it ~

автор: Arif R

11 февр. 2020 г.

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.

автор: Carlos A F

6 февр. 2021 г.

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.

автор: Mimi D

29 июня 2021 г.

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.

автор: Esteban C

24 июля 2020 г.

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

автор: Sandeep K

3 апр. 2022 г.

nice and very informative course

автор: wiky

3 янв. 2019 г.

my favorite and the best course

автор: Hamsini N

3 февр. 2021 г.

Very informative course.

автор: Salvatore M

30 янв. 2016 г.

Thanks - excellent!

автор: julio c r m

11 нояб. 2016 г.

Excellent course .

автор: Kirk G

1 дек. 2016 г.

Very good course

автор: Mac D G

5 февр. 2018 г.


автор: Alejandra R O

4 дек. 2020 г.


автор: Doreen B

5 июня 2019 г.

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.

автор: Adam H

6 февр. 2021 г.

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.

автор: Páidí C

11 мар. 2018 г.

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.

автор: Pooja R

22 июля 2020 г.

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

автор: Dmitry B

28 апр. 2019 г.

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

автор: Alessandro F

17 дек. 2018 г.

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

автор: Alok S

19 окт. 2019 г.

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.

автор: Verena N

22 июня 2022 г.

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)