Plant Bioinformatic Methods Specialization

Instructor: Nicholas James Provart

Skills you'll gain

  •   Scientific Visualization
  •   Data Mining
  •   Data Analysis Software
  •   Analysis
  •   Research Reports
  •   Network Analysis
  •   Bioinformatics
  •   Statistical Analysis
  •   Statistical Methods
  •   Molecular Biology
  •   Data Synthesis
  •   Data Visualization Software
  • Specialization - 4 course series

    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.

    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 BIO101 from Saylor Academy (https://learn.saylor.org/course/view.php?id=349) might be helpful. No programming is required for this course. Bioinformatic Methods I is regularly updated, and was completely updated for January 2024.

    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, dealt with databases, Blast, multiple sequence alignments, phylogenetics, selection analysis and metagenomics. This, the second part, Bioinformatic Methods II, will cover 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. 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 although some command line work (though within a web browser) occurs in the 5th module. Bioinformatic Methods II is regularly updated, and was last updated for January 2024.

    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 [Material updated in June 2024]: Module 1: GENOMIC DBs / PRECOMPUTED GENE TREES / PROTEIN TOOLS. Araport, TAIR, Gramene, EnsemblPlants Compara, PLAZA; SUBA5 and Cell eFP Browser, 1001 Genomes Browser Module 2: EXPRESSION TOOLS. eFP Browser / eFP-Seq Browser, Araport, ARDB, TravaDB, NCBI Genome Data Viewer for exploring RNA-seq data for many plant species, MPSS database for small RNAs Module 3: COEXPRESSION TOOLS. ATTED II, Expression Angler, AraNet, AtCAST2 Module 4: PROMOTER ANALYSIS. Cistome, MEME, 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

    In Plant Bioinformatics on Coursera.org, we covered 33 plant-specific online tools from genome browsers to transcriptomic data mining to promoter/network analyses and others, and in this Plant Bioinformatics Capstone we'll use these tools to hypothesize a biological role for a gene of unknown function, summarized in a written lab report. This course is part of a Plant Bioinformatics Specialization on Coursera, which introduces core bioinformatic competencies and resources, such as NCBI's Genbank, Blast, multiple sequence alignments, phylogenetics in Bioinformatic Methods I, followed by protein-protein interactions, structural bioinformatics and RNA-seq analysis in Bioinformatic Methods II, in addition to the plant-specific concepts and tools introduced in Plant Bioinformatics and the Plant Bioinformatics Capstone. This course/capstone was developed with funding from the University of Toronto's Faculty of Arts and Science Open Course Initiative Fund (OCIF) and was implemented by Eddi Esteban, Will Heikoop and Nicholas Provart. Asher Pasha programmed a gene ID randomizer.

    Bioinformatic Methods II

    Plant Bioinformatics

    Plant Bioinformatics Capstone

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