Nicholas Provart Talks About the Botany Array Resource
Emerging Research FRonts Commentary, April 2011
|
Article: The Botany Array Resource: e-Northerns, Expression Angling, and Promoter analyses
Authors: Toufighi, K;Brady, SM;Austin, R;Ly, E;Provart,
NJ |
Nicholas Provart talks with ScienceWatch.com and answers a few questions about this month's Emerging Research Front paper in the field of Plant & Animal Science.
Why do you think your paper is highly
cited?
The databases and analysis tools described in the original Botany (now Bio-) Array Resource (BAR) paper have found widespread use in the plant biology community, in part because of the fact that they represent some of the first instances of such tools and databases, but also because my lab has continued to add and curate data and to create tools that tap into the BAR database and make the data even more accessible to wet-lab researchers. The tools that comprise the BAR are now used about 60,000 times a month by plant researchers worldwide.
Does it describe a new discovery, methodology, or
synthesis of knowledge?
The BAR paper describes a synthesis of knowledge in the sense of organizing data from different (primary) databases such as TAIR, GO, NASCArrays, etc. such that all information about a gene is available at a user's fingertips, both in a compact overview form, or as a downloadable text file. Additionally, the Expression Angling tool was one of the first to permit easy identification of coexpressed genes in plants. This tool has been used as a "primary screen" for several labs to identify novel genes of interest associated with a given biological process.
Would you summarize the significance of your paper
in layman's terms?
"Due to the ease of generating large datasets, database integration will be increasingly important, perhaps achieved through the use of webservices."
The Bio-Array Resource's significance is that it collates data about where genes are turned on in certain plant tissues, and provides users with tools to easily explore such patterns. Seeing where a gene is active can provide clues as to its function. Additional information (up to 15 different types) are also stored in the BAR database, to provide additional clues towards gene function.
How did you become involved in this research, and
how would you describe the particular challenges, setbacks, and
successes that you've encountered along the way?
I started out doing data analysis in the early 2000s in industry, but was recruited back to academia in 2002—the University of Toronto's plant research group had received a large grant to purchase computational and gene expression profiling infrastructure. A lot of the web tool and algorithm development was new to me, and thus I tended to learn along with the students I was supervising.
One highlight was the creation of our very popular "electronic fluorescent pictograph" tool (Winter et al., 2007, PLoS ONE 2: e718, which uses the BAR's data but displays them in an intuitive pictographic manner. It was so exciting to see it in action the first time! It was created by two very talented undergraduate students and others, and has been cited almost 140 times and used over 1,000,000 times!
Where do you see your research leading in the
future?
Due to the ease of generating large datasets, database integration will be increasingly important, perhaps achieved through the use of web services. I am involved in the International Arabidopsis Informatics Consortium (IAIC, 2010, The Plant Cell 22: 2530-2536), due in part no doubt to the success of the BAR.
The IAIC's goal is to build a new kind of portal for accessing all the different kinds of data that are now available for Arabidopsis and other related species. Wet-lab scientists have expressed frustration with the overwhelming amount of data available, and the proliferation of databases. We hope to make it easy for data providers to plug into our framework.
Do you foresee any social or political
implications for your research?
The availability of large datasets is changing the way scientists do
research. As mentioned above, several groups have used our Expression
Angler tool as a primary screen to identify novel genes associated with
their biological process of interest. I describe this trend in two papers
by Usadel et al. (2010,
Plant Cell and Environment 32:1633-1651)
and Brady & Provart (2009,
The Plant Cell
21:1034-1051).
Nicholas Provart, Ph.D.
Associate Professor, Plant Cyberinfrastructure & Systems Biology
Director, Graduate Program in Genome Biology and Bioinformatics
Chair, Bioinformatics SC, Multinational Arabidopsis Steering
Committee
Member, Centre for the Analysis of Genome Evolution and Function
Department of Cell and Systems Biology
University of Toronto
Toronto, Ontario, Canada
Web |
Web
KEYWORDS: MICROARRAY EXPERIMENT, EXPRESSION PROFILE, PROMOTOR ANALYSIS, ELECTRONIC NORTHERN, DATA MINING, ARABIDOPSIS THALIANA, GENE EXPRESSION, ABSCISIC ACID, 5’ UNTRANSLATED REGION, TRANSCRIPTION FACTORS, INFORMATION RESOURCE, DRAFT SEQUENCE, DATABASE, GENOME.