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.
This course is part of the Plant Bioinformatic Methods Specialization
Offered By
Plant Bioinformatic Methods SpecializationUniversity of TorontoAbout this Course
Learner Career Outcomes
21%
started a new career after completing these courses
25%
got a tangible career benefit from this course
14%
got a pay increase or promotion
Shareable Certificate
Earn a Certificate upon completion
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Start instantly and learn at your own schedule.
Course 1 of 4 in the
Flexible deadlines
Reset deadlines in accordance to your schedule.
Beginner Level
Approx. 20 hours to complete
English
Subtitles: English
Skills you will gain
Genetic AnalysisBioinformatics AnalysisEvolutionComparative Genomics
Learner Career Outcomes
21%
started a new career after completing these courses
25%
got a tangible career benefit from this course
14%
got a pay increase or promotion
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Course 1 of 4 in the
Flexible deadlines
Reset deadlines in accordance to your schedule.
Beginner Level
Approx. 20 hours to complete
English
Subtitles: English
Offered by
University of Toronto
Established in 1827, the University of Toronto is one of the world’s leading universities, renowned for its excellence in teaching, research, innovation and entrepreneurship, as well as its impact on economic prosperity and social well-being around the globe.
Syllabus - What you will learn from this course
3 hours to complete
NCBI/Blast I
In this module we'll be exploring the amazing resources available at NCBI, the National Centre for Biotechnology Information, run by the National Library of Medicine in the USA. We'll also be doing a Blast search to find similar sequences in the enormous NR sequence database. We can use similar sequences to infer homology, which is the primary predictor of gene or protein function.
3 hours to complete
4 videos (Total 52 min), 4 readings, 1 quiz
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
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
1 hour to complete
Review: NCBI/Blast I, Blast II/Comparative Genetics, and Multiple Sequence Alignments
1 hour to complete
Reviews
TOP REVIEWS FROM BIOINFORMATIC METHODS I
by SAJul 11, 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.
by EDApr 26, 2017
Great course. All lectures provide a biological context for the tools you learn in the labs. The labs themselves provide a great introduction to the many tools available for bioinformatic analysis.
by FJFeb 5, 2017
The videos were very clear on how to use various bioinformatic tools. I found no difficulty in understanding them. Really enjoyed the course. Looking forward to the next part of this course!
by RGNov 4, 2017
I enjoyed doing the course. It is exciting to see how much one can learn from a few gene or protein sequences. Thank you for making the course understandable to a beginner in bioinformatics!
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.
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