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.
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- Genetic Analysis
- Bioinformatics Analysis
- Evolution
- Comparative Genomics
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토론토 대학교
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.
강의 계획표 - 이 강좌에서 배울 내용
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.
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.
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.
Review: NCBI/Blast I, Blast II/Comparative Genetics, and Multiple Sequence Alignments
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- 5 stars77.02%
- 4 stars18.59%
- 3 stars3.41%
- 2 stars0.38%
- 1 star0.57%
BIOINFORMATIC METHODS I의 최상위 리뷰
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!
Explanation was on point. As a beginner didn't have to face much problem to understand terminologies and concepts and PDF of the study materials played an important role to understand.
Great tour through the main areas of bioinformatics. I learned to use a lot of powerful tools for bioinformatic analyses as well as important topics like phylogenetics and metagenomics.
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)
Plant Bioinformatic Methods 특화 과정 정보
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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