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Plant Bioinformatic Methods

Nicholas James Provart

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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What's inside

Four courses

Bioinformatic Methods I

(3 hours)
Large-scale biology projects have created a wealth of data for biologists. This course focuses on employing existing bioinformatic resources to access this data and extract useful information. Topics covered include multiple sequence alignments, phylogenetics, gene expression data analysis, and protein interaction networks.

Bioinformatic Methods II

(3 hours)
Large-scale biology projects have created a wealth of data for biologists. This course focuses on employing existing bioinformatic resources to access this data to answer questions relevant to the average biologist. Topics covered include motif searching, protein-protein interactions, structural bioinformatics, gene expression data analysis, and cis-element predictions.

Plant Bioinformatics

(0 hours)
The past 15 years have been exciting for 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 allow us to generate hypotheses at the click of a mouse.

Plant Bioinformatics Capstone

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.

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