2 minute intro, a
20 minute theory mini-lecture, a 1.5 hour hands-on lab, an optional
20 minute lab discussion if experiencing difficulties with lab, and a
2 minute summary. Tools covered: Module 1: GENOMIC DBs / PRECOMPUTED GENE TREES / PROTEIN TOOLS. Araport, TAIR, Gramene, EnsemblPlants Compara, PLAZA; SUBA4 and Cell eFP Browser, 1001 Genomes Browser Module 2: EXPRESSION TOOLS. eFP Browser / eFP-Seq Browser, Araport, Genevestigator, TravaDB, NCBI Genome Data Viewer for exploring RNA-seq data for many plant species other than Arabidopsis, MPSS database for small RNAs Module 3: COEXPRESSION TOOLS. ATTED II, Expression Angler, AraNet, AtCAST2 Module 4: PROMOTER ANALYSIS. Cistome, Athena, ePlant Module 5: GO ENRICHMENT ANALYSIS AND PATHWAY VIZUALIZATION. AgriGO, AmiGO, Classification SuperViewer, TAIR, g:profiler, AraCyc, MapMan (optional: Plant Reactome) Module 6: NETWORK EXPLORATION. Arabidopsis Interactions Viewer 2, ePlant, TF2Network, Virtual Plant, GeneMANIA [Material updated in June 2019]
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. For instance, knowing where and when a gene is expressed can help us narrow down the phenotypic search space when we don't see a phenotype in a gene mutant under \"normal\" growth conditions. Coexpression analyses and association networks can provide high-quality candidate genes involved in a biological process of interest. Using Gene Ontology enrichment analysis and pathway visualization tools can help us make sense of our own 'omics experiments and answer the question \"what processes/pathways are being perturbed in our mutant of interest?\" Structure: each of the 6 week hands-on modules consists of a
2 minute intro, a
20 minute theory mini-lecture, a 1.5 hour hands-on lab, an optional
20 minute lab discussion if experiencing difficulties with lab, and a
2 minute summary. Tools covered: Module 1: GENOMIC DBs / PRECOMPUTED GENE TREES / PROTEIN TOOLS. Araport, TAIR, Gramene, EnsemblPlants Compara, PLAZA; SUBA4 and Cell eFP Browser, 1001 Genomes Browser Module 2: EXPRESSION TOOLS. eFP Browser / eFP-Seq Browser, Araport, Genevestigator, TravaDB, NCBI Genome Data Viewer for exploring RNA-seq data for many plant species other than Arabidopsis, MPSS database for small RNAs Module 3: COEXPRESSION TOOLS. ATTED II, Expression Angler, AraNet, AtCAST2 Module 4: PROMOTER ANALYSIS. Cistome, Athena, ePlant Module 5: GO ENRICHMENT ANALYSIS AND PATHWAY VIZUALIZATION. AgriGO, AmiGO, Classification SuperViewer, TAIR, g:profiler, AraCyc, MapMan (optional: Plant Reactome) Module 6: NETWORK EXPLORATION. Arabidopsis Interactions Viewer 2, ePlant, TF2Network, Virtual Plant, GeneMANIA [Material updated in June 2019]
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. For instance, knowing where and when a gene is expressed can help us narrow down the phenotypic search space when we don't see a phenotype in a gene mutant under \"normal\" growth conditions. Coexpression analyses and association networks can provide high-quality candidate genes involved in a biological process of interest. Using Gene Ontology enrichment analysis and pathway visualization tools can help us make sense of our own 'omics experiments and answer the question \"what processes/pathways are being perturbed in our mutant of interest?\" Structure: each of the 6 week hands-on modules consists of a
2 minute intro, a
20 minute theory mini-lecture, a 1.5 hour hands-on lab, an optional
20 minute lab discussion if experiencing difficulties with lab, and a
2 minute summary. Tools covered: Module 1: GENOMIC DBs / PRECOMPUTED GENE TREES / PROTEIN TOOLS. Araport, TAIR, Gramene, EnsemblPlants Compara, PLAZA; SUBA4 and Cell eFP Browser, 1001 Genomes Browser Module 2: EXPRESSION TOOLS. eFP Browser / eFP-Seq Browser, Araport, Genevestigator, TravaDB, NCBI Genome Data Viewer for exploring RNA-seq data for many plant species other than Arabidopsis, MPSS database for small RNAs Module 3: COEXPRESSION TOOLS. ATTED II, Expression Angler, AraNet, AtCAST2 Module 4: PROMOTER ANALYSIS. Cistome, Athena, ePlant Module 5: GO ENRICHMENT ANALYSIS AND PATHWAY VIZUALIZATION. AgriGO, AmiGO, Classification SuperViewer, TAIR, g:profiler, AraCyc, MapMan (optional: Plant Reactome) Module 6: NETWORK EXPLORATION. Arabidopsis Interactions Viewer 2, ePlant, TF2Network, Virtual Plant, GeneMANIA [Material updated in June 2019]
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The students of this course have found this course easy.
Assignments
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Certification
You will get a certificate on completing this course.
University
The course is from one of the top universities of the world - University of Toronto.
Price
This course costs very less.
Difficulty
The students of this course have found this course easy.
Assignments
The students of this course have liked the assignments of this course.
Teaching
The students of this course have liked how the instructor has taught this course.
Satisfaction
The students of this course are overall satisfied with this course.
Edvicer's Rewards
You can get a cashback of ₹ 100 on buying this course.
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. For instance, knowing where and when a gene is expressed can help us narrow down the phenotypic search space when we don't see a phenotype in a gene mutant under "normal" growth conditions. Coexpression analyses and association networks can provide high-quality candidate genes involved in a biological process of interest. Using Gene Ontology enrichment analysis and pathway visualization tools can help us make sense of our own 'omics experiments and answer the question "what processes/pathways are being perturbed in our mutant of interest?" Structure: each of the 6 week hands-on modules consists of a
2 minute intro, a
20 minute theory mini-lecture, a 1.5 hour hands-on lab, an optional
20 minute lab discussion if experiencing difficulties with lab, and a
2 minute summary. Tools covered: Module 1: GENOMIC DBs / PRECOMPUTED GENE TREES / PROTEIN TOOLS. Araport, TAIR, Gramene, EnsemblPlants Compara, PLAZA; SUBA4 and Cell eFP Browser, 1001 Genomes Browser Module 2: EXPRESSION TOOLS. eFP Browser / eFP-Seq Browser, Araport, Genevestigator, TravaDB, NCBI Genome Data Viewer for exploring RNA-seq data for many plant species other than Arabidopsis, MPSS database for small RNAs Module 3: COEXPRESSION TOOLS. ATTED II, Expression Angler, AraNet, AtCAST2 Module 4: PROMOTER ANALYSIS. Cistome, Athena, ePlant Module 5: GO ENRICHMENT ANALYSIS AND PATHWAY VIZUALIZATION. AgriGO, AmiGO, Classification SuperViewer, TAIR, g:profiler, AraCyc, MapMan (optional: Plant Reactome) Module 6: NETWORK EXPLORATION. Arabidopsis Interactions Viewer 2, ePlant, TF2Network, Virtual Plant, GeneMANIA [Material updated in June 2019]
Plant Genomic Databases, and useful sites for info about proteins
Expression Analysis
Coexpression Tools
Sectional Quiz 1
Promoter Analysis
Functional Classification and Pathway Vizualization
Network Exploration (PPIs, PDIs, GRNs)
Sectional Quiz 2 and Final Assignment
Reviews from Coursera
Overall the course is good. However, lecture should be more in detail.
Very good course for mastering bioinformatics skills. Genetics and molecular biology students/professionals should take this course to augment their research skills.
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.
I really enjoyed the course. Got teary eyed after finishing the course. I really put my extra time in this course and I learned so much. Thank you
A really enjoyable and interesting course, well taught. I really enjoyed working through the lab practicals, getting hands on experience with many of the tools used for plant bioinformatics was a good Read More ...
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