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Voltar para Métodos de bioinformática I

Comentários e feedback de alunos de Métodos de bioinformática I da instituição Universidade de Toronto

4.7
estrelas
1,500 classificações
342 avaliações

Sobre o curso

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 (this one), deals with databases, Blast, multiple sequence alignments, phylogenetics, selection analysis and metagenomics. The second part, Bioinformatic Methods II, covers 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. Both provide an overview of the many different bioinformatic tools that are out there. 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. Bioinformatic Methods I is regularly updated, and was completely updated for January 2022....

Melhores avaliações

SA
11 de Jul de 2020

This course is very well organized, easy to understand, and explained everything steps by step which will help to grasp the concept easily. If you are a beginner like me, you should take this course.

BA
2 de Nov de 2021

Bioinformatics 1 was very interesting and enlightening for me. I learnt practical skills which I can now apply in to ace an impactful career. Thank you so much Coursera for this amazing opportunity!

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101 — 125 de 335 Avaliações para o Métodos de bioinformática I

por Shamsunnahar M

17 de Set de 2019

I had a very basic knowledge but this course help me to understand the use of all parameters and what is the objective for this.

por Anuj S

17 de Jan de 2021

This course is very helpful in related to providing basic knowledge about the topic and that is best thing about this course.

por Sael M A

5 de Dez de 2017

Great course fro beginners, highly recommended for people who are going to have some bioinformatic aspects in their projects.

por Vitor I

5 de Jan de 2021

Nicholas Provart is a great instructor!

This course was very useful. I'll highly recommend other students to take this course

por Wambui K

14 de Nov de 2018

The course was excellent. The labs give a practical feel of what Bioinformatics is. Great work. Looking forward to Part II.

por Jegadishwar A N

7 de Ago de 2021

Nice course. Very well explained. Interesting topic shown in an equally interesting manner. Tools shown also very useful

por Roman P

4 de Nov de 2018

bioinformatics guide for practical work, great observation of last common use programs and clear explanation of methods

por Gulnaz D

1 de Set de 2020

Thank you very much for this course! This course was extremely interesting !

I enriched my knowledge in Bioinformatics.

por omar w

17 de Ago de 2019

this course's lab is really amazing the only thing id recommend is to increase the number of questions in weekly tests

por Suhas G

6 de Nov de 2016

A very well structured course with graded difficulty and accurate instructions. Throughly enjoyed being a part of it.

por Cristi V

14 de Mar de 2016

Great and indepth introduction for those interested in learning bioinformatics. Next stop: Bioinformatic Methods II

por Ivana R

21 de Jun de 2017

All lectures are well explained and in proper construction. Lab discussions help to internalize the material well.

por Atakan z N

15 de Dez de 2020

I learned how to analyze by using bioinformatics data with taxonomy. My perspective has changed with new programs

por Anna A

24 de Ago de 2020

Instructions for the assignments are very straightforward, which helped a lot to build my skill step by step.

por Roman S

8 de Jan de 2017

It was a relevant course teaching basic bioinformatics. the course was well-structured and not hard-to follow

por Shreya P

30 de Set de 2020

Very well explained all the topics..

Plus it is great to attend those quiz after completing one week cource.

por Negar P

14 de Set de 2015

It is very useful and helpful. Thank you very much Coursera and special thanks to dear Dr. Nicholas Provart.

por Md. M R B

14 de Ago de 2020

If you have a keen interest in Bioinformatics then this course is for you and trust me this course is best.

por Waseem A A

2 de Mai de 2020

Vey well-designed, very informative, and interesting. One of the best online courses about Bioinformatics.

por Roberto I L C

17 de Ago de 2019

Amazing and well explained course...Lot of themes and information, some easy/difficult quizzes questions.

por Muhammad Z M

29 de Jun de 2018

thanku so much for this course really the mentor nicholas is a great teacher and i have enjoy the course.

por Muhammad F N

6 de Jul de 2020

I m a bioinformatician, this course helped me acquire better skills and understanding of bioinformatics.

por Pavithrra G

20 de Jun de 2017

I can understand each and everything clearly, really a good course for basic learners in Bioinformatics.

por Aswini P V

4 de Ago de 2020

Thanks for this Cousera. Kindly , offer some more free course , in order to feed poor classed student.

por Mesut O

27 de Out de 2018

Assessments were stressful. I felt that I've learned the some fundamentals of Computational Biology