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Вернуться к Bioinformatic Methods II

Bioinformatic Methods II, University of Toronto

4.7
Оценки: 180
Рецензии: 36

Об этом курсе

Large-scale biology projects such as the sequencing of the human genome and gene expression surveys using RNA-seq, microarrays and other technologies have created a wealth of data for biologists. However, the challenge facing scientists is analyzing and even accessing these data to extract useful information pertaining to the system being studied. This course focuses on employing existing bioinformatic resources – mainly web-based programs and databases – to access the wealth of data to answer questions relevant to the average biologist, and is highly hands-on. Topics covered include multiple sequence alignments, phylogenetics, gene expression data analysis, and protein interaction networks, in two separate parts. The first part, Bioinformatic Methods I, dealt with databases, Blast, multiple sequence alignments, phylogenetics, selection analysis and metagenomics. This, the second part, Bioinformatic Methods II, will cover motif searching, protein-protein interactions, structural bioinformatics, gene expression data analysis, and cis-element predictions. This pair of courses is useful to any student considering graduate school in the biological sciences, as well as students considering molecular medicine. These courses are based on one taught at the University of Toronto to upper-level undergraduates who have some understanding of basic molecular biology. If you're not familiar with this, something like https://learn.saylor.org/course/bio101 might be helpful. No programming is required for this course although some command line work (though within a web browser) occurs in the 5th module....

Лучшие рецензии

автор: RG

Apr 06, 2017

Gives the student real world exposure to the tools to study proteins gene regulation, etc. Instructor is involved and friendly. Highly recommended for someone who is interested in contemporary

автор: NM

Jan 09, 2018

Hi Nicholas, Thank you so much for giving a lot of information. Bioinformatic Methods II was little difficult but understood after repeating the lad discussions. Thanks a lot.

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Рецензии: 35

автор: Catalin Pesecan

Sep 01, 2018

Quite good introductory course for Bioinformatics.

автор: Mariano Ruben Rodriguez Sosa

Aug 20, 2018

It was a very complete course to understand protein interaction and how to use data bases to quantify it

I recommend this course to every master student doing molecular biology or genetics.

автор: Katherine Gabriela Briceño Leal

Apr 01, 2018

I just loved the course, I learned several tools in a short time and I hope to take advantage of them in the future. This course encouraged me to continue with similar ones.

Many thanks to Professor Provart, for his simple way of explaining, I hope he continues to dictate other courses in the future.

автор: Nissi Paul. M

Jan 09, 2018

Hi Nicholas, Thank you so much for giving a lot of information. Bioinformatic Methods II was little difficult but understood after repeating the lad discussions. Thanks a lot.

автор: Padma Srinivasan

Sep 16, 2017

An amazing course....highly recommended.

автор: Rajeswara Reddy Erva

Sep 06, 2017

Truly Knowledgeable course........

автор: José Luis Villalpando Aguilar

Sep 02, 2017

Excellent!

автор: MAHAMADOU ADAMOU Nassirou

Jul 16, 2017

Thanks a lot! Thanks for the time spent to teach us this Nice Bioinformatic Methods II!

автор: Kolchenko Sergey

Jul 15, 2017

This was extremely usefull course for me. The only thing I can suggest is making a small course book with all methods from this course. As for assignments, probably it could be better no include more questions to it, like it has been done in lab notes, not just five.

автор: Alexander Koval

Jun 08, 2017

It is excellent and absorbing cource of bioinformatics. I enjoyed it a lot: many interesting and complex topics are explained by Prof. Provart. And almost everything becomes clear.

Only one topic was significantly difficult for me - the topic about gene expression, where R programming is applied. Some commands work only in online version of R. I nees some more time to realize the algorithm of this magic.

I recommend this course for most advanced students of medical university, and they have been expanded their horizonts of understanding biochemistry.