About this Course
최근 조회 5,276

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

중급 단계

None required but you should be familiar with basic aspects of plant and molecular biology. Bioinformatic Methods I and II would be good preparation

완료하는 데 약 11시간 필요

권장: 6 weeks of hands-on study, plus 2 evaluation weeks. The hands-on modules will take 2-4 hours of time...

영어

자막: 영어

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

중급 단계

None required but you should be familiar with basic aspects of plant and molecular biology. Bioinformatic Methods I and II would be good preparation

완료하는 데 약 11시간 필요

권장: 6 weeks of hands-on study, plus 2 evaluation weeks. The hands-on modules will take 2-4 hours of time...

영어

자막: 영어

강의 계획 - 이 강좌에서 배울 내용

1
완료하는 데 3시간 필요

Plant Genomic Databases, and useful sites for info about proteins

In this module we'll be exploring several plant databases including Ensembl Plants, Gramene, PLAZA, SUBA, TAIR and Araport. The information in these databases allows us to easily identify functional regions within gene products, view subcellular localization, find homologs in other species, and even explore pre-computed gene trees to see if our gene of interest has undergone a gene duplication event in another species, all at the click of a mouse!

...
4 videos (Total 44 min), 4 readings, 1 quiz
4개의 동영상
Mini-lecture17m
Lab Discussion23m
Summary1m
4개의 읽기 자료
Acknowledgements10m
Course Logistics10m
Mini-lecture Notes10m
Lab 1 -- Plant Genomic Databases and Tools for Exploring Protein Information1시 30분
1개 연습문제
Lab Quiz 1
2
완료하는 데 2시간 필요

Expression Analysis

Vast databases of gene expression and nifty visualization tools allow us to explore where and when a gene is expressed. Often this information can be used to help guide a search for a phenotype if we don't see a phenotype in a gene mutant under "normal" growth conditions. We explore several tools for Arabidopsis data (eFP Browser, Genevestigator, TraVA DB, Araport) along with NCBI's Genome Data Viewer for RNA-seq data for other plant species. We also examine the MPSS database of small RNAs and degradation products to see if our example gene has any potential microRNA targets.

...
4 videos (Total 38 min), 2 readings, 1 quiz
4개의 동영상
Mini-lecture17m
Lab Discussion18m
Summary50
2개의 읽기 자료
Mini-lecture Notes10m
Lab 2 -- Expression Analysis1시 30분
1개 연습문제
Lab Quiz 2
3
완료하는 데 2시간 필요

Coexpression Tools

Being able to group genes by similar patterns of expression across expression data sets using algorithms like WGCNA is a very useful way of organizing the data. Clusters of genes with similar patterns of expression can then be subject to Gene Ontology term enrichment analysis (see Module 5) or examined to see if they are part of the same pathway. What's even more powerful is being able to identify genes with similar patterns of expression without doing a single expression profiling experiment, by mining gene expression databases! There are several tools that allow you to do this in many plant species simply by entering a query gene identifier. The genes that are returned are often in the same biological process as the query gene, and thus this "guilt-by-association" paradigm is a excellent tool for hypothesis generation.

...
4 videos (Total 29 min), 2 readings, 1 quiz
4개의 동영상
Mini-lecture9m
Lab Discussion16m
Summary49
2개의 읽기 자료
Mini-lecture Notes10m
Lab 3 -- Coexpression Tools1시 30분
1개 연습문제
Lab Quiz 3
4

Sectional Quiz 1

...
1 quiz
1개 연습문제
Sectional Quiz 1
5
완료하는 데 2시간 필요

Promoter Analysis

The regulation of gene expression is one of the main ways by which a plant can control the abundance of a gene product (post-translational modifications and protein degradation are some others). When and where a gene is expressed is controlled to a large extent by the presence of short sequence motifs, called cis-elements, present in the promoter of the gene. These in turn are regulated by transcription factors that perhaps get induced in response to environmental stresses or during specific developmental programs. Thus understanding which transcription factors can bind to which promoters can help us understand the role the downstream genes might be playing in a biological system.

...
4 videos (Total 32 min), 2 readings, 1 quiz
4개의 동영상
Mini-lecture17m
Lab Discussion12m
Summary49
2개의 읽기 자료
Mini-lecture Notes10m
Lab 4 -- Promoter Analysis1시 30분
1개 연습문제
Lab Quiz 4
6
완료하는 데 2시간 필요

Functional Classification and Pathway Vizualization

Often the results of 'omics experiments are large lists of genes, such as those that are differentially expressed. We can use a "cherry picking" approach to explore individual genes in those lists but it's nice to be able to have an automated way of analyzing them. Here tools for performing Gene Ontology enrichment analysis are invaluable and can tell you if any particular biological processes or molecular functions are over-represented in your gene list. We'll explore AgriGO, AmiGO, tools at TAIR and the BAR, and g:Profiler, which all allow you to do such analyses. Another useful analysis is to be able to map your gene lists (along with associated e.g. expression values) onto pathway representations, and we'll use AraCyc and MapMan to do this. In this way it is easy to see if certain biosynthetic reactions are upregulated, which can help you interpret your 'omics data!

...
4 videos (Total 32 min), 2 readings, 1 quiz
4개의 동영상
Mini-lecture13m
Lab Discussion15m
Summary46
2개의 읽기 자료
Mini-lecture Notes10m
Lab 5 -- Functional Classification and Pathway Visualization1시 30분
1개 연습문제
Lab Quiz 5
7
완료하는 데 2시간 필요

Network Exploration (PPIs, PDIs, GRNs)

Molecules inside the cell rarely operate in isolation. Proteins act together to form complexes, or are part of signal transduction cascades. Transcription factors bind to cis-elements in promoters or elsewhere and can act as activators or repressors of transcription. MicroRNAs can affect transcription in other ways. One of the main themes to have emerged in the past two decades in biology is that of networks. In terms of protein-protein interaction networks, often proteins that are highly connected with others are crucial for biological function – when these “hubs” are perturbed, we see large phenotypic effects. The way that transcription factors interact with downstream promoters, some driving the expression of other transcription factors that in turn regulate genes combinatorially with upstream transcription factors can have an important biological effect in terms of modulating the kind of output achieved. The tools described in this lab can help us to explore molecular interactions in a network context, perhaps with the eventual goal of modeling the behaviour of a given system.

...
4 videos (Total 34 min), 2 readings, 1 quiz
4개의 동영상
Mini-lecture18m
Lab Discussion13m
Summary1m
2개의 읽기 자료
Mini-lecture Notes10m
Lab 6 -- Network Exploration (PPIs, PDIs, GRNs)1시 30분
1개 연습문제
Lab Quiz 6
8

Sectional Quiz 2 and Final Assignment

...
2 quizzes
2개 연습문제
Sectional Quiz 2
Final Assignment
4.8
8개의 리뷰Chevron Right

Plant Bioinformatics의 최상위 리뷰

대학: QRMar 10th 2019

Very good course for mastering bioinformatics skills. Genetics and molecular biology students/professionals should take this course to augment their research skills.

대학: FSFeb 22nd 2019

Professor Provart is very good and the labs taught us in simple and direct instructions how to perform a wide range of analysis regarding Plant Bioinformatics.

강사

Avatar

Nicholas James Provart

Professor
Cell & Systems Biology

토론토 대학교 정보

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. ...

자주 묻는 질문

  • 강좌에 등록하면 바로 모든 비디오, 테스트 및 프로그래밍 과제(해당하는 경우)에 접근할 수 있습니다. 상호 첨삭 과제는 이 세션이 시작된 경우에만 제출하고 검토할 수 있습니다. 강좌를 구매하지 않고 살펴보기만 하면 특정 과제에 접근하지 못할 수 있습니다.

  • 수료증을 구매하면 성적 평가 과제를 포함한 모든 강좌 자료에 접근할 수 있습니다. 강좌를 완료하면 전자 수료증이 성취도 페이지에 추가되며, 해당 페이지에서 수료증을 인쇄하거나 LinkedIn 프로필에 수료증을 추가할 수 있습니다. 강좌 콘텐츠만 읽고 살펴보려면 해당 강좌를 무료로 청강할 수 있습니다.

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