This course is part of the Plant Bioinformatic Methods Specialization

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Nicholas James Provart

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Plant Bioinformatic Methods SpecializationUniversity of Toronto

About this Course

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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 2023.

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Course 1 of 4 in the

Plant Bioinformatic Methods Specialization

Beginner Level

Approx. 19 hours to complete

English

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Skills you will gain

Genetic Analysis
Bioinformatics Analysis
Evolution
Comparative Genomics

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Course 1 of 4 in the

Plant Bioinformatic Methods Specialization

Beginner Level

Approx. 19 hours to complete

English

Could your company benefit from training employees on in-demand skills?

Try Coursera for Business

Instructor

Instructor rating

4.74/5 (354 Ratings)

Nicholas James Provart

Professor

Cell & Systems Biology

112,764 Learners

4 Courses

Offered by

University of Toronto

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Syllabus - What you will learn from this course

Content Rating98%(9,088 ratings)

Week1

Week 1

3 hours to complete

NCBI/Blast I

3 hours to complete

4 videos (Total 52 min), 4 readings, 1 quiz

Week2

Week 2

3 hours to complete

Blast II/Comparative Genomics

In this module we'll continue exploring the incredible resources available at NCBI, the National Centre for Biotechnology Information. We will be performing several different kinds of Blast searches: BlastP, PSI-Blast, and Translated Blast. We can use similar sequences identified by such methods to infer homology, which is the primary predictor of gene or protein function. We'll also be comparing parts of the genomes of a couple of different species, to see how similar they are.

3 hours to complete

4 videos (Total 58 min), 2 readings, 1 quiz

Week3

Week 3

3 hours to complete

Multiple Sequence Alignments

In this module we'll be doing multiple sequence alignments with Clustal and MUSCLE (as implemented in MEGA), and MAFFT. Multiple sequences alignments can tell you where in a sequence the conserved and variable regions are, which is important for understanding the biology of the sequences under investigation. It also has practical applications, such as being able to design PCR primers that will amplify sequences from a number of different species, for example.

3 hours to complete

4 videos (Total 46 min), 2 readings, 1 quiz

Week4

Week 4

1 hour to complete

Review: NCBI/Blast I, Blast II/Comparative Genetics, and Multiple Sequence Alignments

1 hour to complete

Week5

Week 5

3 hours to complete

Phylogenetics

3 hours to complete

4 videos (Total 43 min), 2 readings, 1 quiz

Week6

Week 6

3 hours to complete

Selection Analysis

In this module we'll take a set of orthologous sequences from bacteria and use DataMonkey to analyze them for the presence of certain sites under positive, negative or neutral selection. Such an analysis can help understand the biology of a set of protein coding sequences by identifying residues that might be important for biological function (those residues under negative selection) or those that might be involved in response to external influences, such as drugs, pathogens or other factors (residues under positive selection).

3 hours to complete

4 videos (Total 39 min), 2 readings, 1 quiz

Week7

Week 7

3 hours to complete

'Next Gen' Sequence Analysis (RNA-Seq) / Metagenomics

In this module we'll explore some of the data that have been generated as a result of the rapid decrease in the cost of sequencing DNA. We'll be exploring a couple of RNA-Seq data sets that can tell us where any given gene is expressed, and also how that gene might be alternatively spliced. We'll also be looking at a couple of metagenome data sets that can tell us about the kinds of species (especially microbial species that might otherwise be hard to culture) that are in a given environmental niche.

3 hours to complete

4 videos (Total 52 min), 2 readings, 1 quiz

Week8

Week 8

1 hour to complete

Review: Phylogenetics, Selection Analysis, and 'Next Gen' Sequence Analysis (RNA-seq)/Metagenomics + Final Assignment

1 hour to complete

1 reading

Reviews

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TOP REVIEWS FROM BIOINFORMATIC METHODS I

by NSOct 2, 2015

A thorough course for beginners with very interesting labs! I was pleasantly surprised with how much and how easily I learned bioinformatics skills with this course. Well done!

by RQDec 13, 2020

Great Course. I love the way it is designed, delivered. I learned a lot. The most important part is that I enjoy every bit of the session and completed everything for less than a week. :)

by PGJan 21, 2019

This course is so accurate and useful to the bioinformatic students and the science students who needs help with the computational biology. I would recommend this course to everyone.

by DAJan 31, 2020

Procedures are very well explained. Would be helpful to have some pipeline diagrams on the best way (software and breif methods) to solve a problem (e.g. for the assignment)

View all reviews

About the Plant Bioinformatic Methods Specialization

The past 15 years have been exciting ones in plant biology. Hundreds of plant genomes have been sequenced, RNA-seq has enabled transcriptome-wide expression profiling, and a proliferation of "-seq"-based methods has permitted protein-protein and protein-DNA interactions to be determined cheaply and in a high-throughput manner. These data sets in turn allow us to generate hypotheses at the click of a mouse or tap of a finger.The Plant Bioinformatics Specialization on Coursera introduces core bioinformatic competencies and resources, such as NCBI's Genbank, Blast, multiple sequence alignments, phylogenetics in Bioinformatic Methods I, followed by protein-protein interaction, structural bioinformatics and RNA-seq analysis in Bioinformatic Methods II. In Plant Bioinformatics we cover 33 plant-specific online tools from genome browsers to transcriptomic data mining to promoter/network analyses and others. Last, a Plant Bioinformatics Capstone uses these tools to hypothesize a biological role for a gene of unknown function, summarized in a written lab report.This specialization is useful to any modern plant molecular biologist wanting to get a feeling for the incredible scope of data available to researchers. A small amount of R programming is introduced in Bioinformatic Methods II, but most of the tools are web applications. It is recommended that you have access to a laptop or desktop computer for running these as they may not work as mobile applications on your phone or tablet.

Frequently Asked Questions

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Bioinformatic Methods I

About this Course

Skills you will gain