Prediction of Plant Protein Subcellular Locations

Title : Prediction of Plant Protein Subcellular Locations

Abstract:

There are many thousands of proteins in a plant cell. The subcellular locations of proteins determine where the proteins play their biological roles. Prediction and curation of protein subcellular locations are essential for protein functional annotation. We evaluated a number of prediction tools and developed an accurate protocol for predicting protein subcellular locations in plants, and then using the protocol we constructed he Plant Secretome and Subcellular Proteome KnowledgeBase (PlantSecKB) for the plant research community to access and curate plant protein subcellular locations. The database is constructed with all the available plant protein data retrieved from the UniProtKB database and plant protein sequences predicted from EST data assembled by the PlantGDB project. The categories of subcellular locations include secretome, mitochondria, chloroplast, cytosol, cytoskeleton, endoplasmic reticulum, Golgi apparatus, lysosome, peroxisome, nucleus, vacuole, and plasma membrane.  The data can be searched by using UniProt accession number or ID, GenBank GI or RefSeq accession number, gene name, and keywords.  Species specific secretome and subcellular proteomes can be searched and downloaded into a FASTA file.  BLAST is available to allow users to search the database based on protein sequences. Community curation for subcellular locations of plant proteins is also supported. This database aims to facilitate plant protein research and is available at http://bioinformatics.ysu.edu/secretomes/plant/index.php

Take Away Notes:
• The audience will learn how to predict the subcellular locations of their proteins.
• The audience will learn how to use the PlantSecKB database to search for their protein subcellular locations.
• The audience will be able to use the system to deposit the subcellular locations of their proteins into the database for public access.
• The database contains 1.4 millions of proteins with predicted subcellular locations and can be a good resource for research and teaching.

Biography:

Dr. Min graduated with a Ph. D. degree at the University of Hawaii in 1995. He did the postdoctoral research at the University of British Columbia, Canada, and the Research Institute of Physics and Chemistry (RIKEN), Japan.  He worked as a research associate at Concordia University, Canada.  He currently works as a professor at Youngstown State University, USA. He has been working in the areas of plant physiology, plant genomics, and bioinformatics.  He developed some well-used software tools and databases including OrfPrdictor, FunSecKB, PlantSecKB, etc. He has published more than 50 research articles and served as an editor for several scientific journals such as PlosONE.