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Learner Reviews & Feedback for Bioinformatic Methods II by University of Toronto

4.7
stars
471 ratings

About the Course

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. Bioinformatic Methods II is regularly updated, and was last updated for January 2023....

Top reviews

RG

Apr 5, 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

MR

Aug 19, 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.

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51 - 75 of 77 Reviews for Bioinformatic Methods II

By Harini

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Jun 23, 2020

It's is very useful

By Emad R

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Jan 27, 2022

This is very good.

By Shawn B C

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Oct 19, 2021

Very informational

By PAULA A

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Jul 8, 2022

Excelente curso!

By Vasantha S V

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Dec 15, 2020

excellent course

By shikha K

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Jan 17, 2019

very good course

By Juan R T

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Oct 2, 2015

Excellent course

By Sharem M

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Feb 23, 2016

Awesome Course!

By Deepthi g

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Aug 29, 2021

very useful!!!

By Marina R V

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Oct 8, 2020

Muy formativo

By yaohuan23

•

Feb 1, 2016

excellent job

By Dina A M A

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Jun 27, 2019

very great

By jose l V

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Sep 2, 2017

Excellent!

By Emilio F V

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Aug 10, 2022

Excellent

By Aasim M

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Sep 15, 2020

Excellent

By José P C I

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Nov 15, 2015

The best.

By Nammi S K

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Jun 16, 2020

Good

By Randy M

•

Nov 19, 2020

A++

By Shaurav B

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Nov 14, 2020

The course content is good and i came to know about many protein structure prediction and analysis bioinformatic tools and gene expression and analysis tools, The course is designed very systematically but the instuctor went through the explanation videos a bit fast. Overall the course structure is good.

By Sergey K

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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.

By Nazia T F

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May 21, 2020

The course is good overall except for the part of using R commands. I have learned many new things. I especially liked the final assignment part.

By Lucas A C

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Jul 28, 2020

An excellent course, but the activities with R requiere more in depth explanation of the functions and the R language.

By Raghavendra G

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Jul 25, 2020

Lectures were very informative, but some (gene expression analysis) lab exercises need more explanation

By Catalin P

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Sep 1, 2018

Quite good introductory course for Bioinformatics.

By Anne-Karina P

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Oct 29, 2015

introduction to many useful online data resources