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Paul Shaw

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Staff picture: Paul Shaw
Information and Computational Sciences
Paul.Shaw@hutton.ac.uk
+44 (0)1382 568864

The James Hutton Institute
Invergowrie
Dundee DD2 5DA
Scotland UK

  • 2011 - present: Database Developer / Computational Biologist - The James Hutton Institute
  • 2009-2015 - PhD Computational Sciences - The James Hutton Institute and Edinburgh Napier University
  • 2002 - 2011: Bioinformatics Database Developer, Genetics Programme, The Scottish Crop Research Institute
  • 1999-2002: Bioinformatics Programmer - Roslin Institute, Edinburgh.
  • 1998 - 1999 MSc Bioinformatics
  • 1994-1998 BSc (Hons) Microbial Biotechnology

Current research interests 

  • Plant pedigree visualization.
  • Development of the Germinate platform.
  • Development of bespoke applications to support the storage, manipulation and visualisation of biological data and new high throughput genotyping technologies.

The increasingly diverse range of data-types that are being used in modern plant genetics is a problem, both how data is stored, and how scientists can query and visualize in scientifically meaningful ways. My primary research focus is on how we efficiently store and query large datasets and investigating how user interfaces can allow researchers access to this data in ways that allow increased scientific value to be gained. I am particularly interested in how we can increase the overall data quality of data-sets through error identification and the development of electronic data capture and reference applications (mobile based) to aid field scientists. Any problems we can reduce at the data capture stage ensures high data quality for downstream processing and analysis.

A main focus of my work is in the development of complex online databases implemented in MySQL for the dissemination of data to both internal and external (academic and industrial) audiences and the development of the supporting programming infrastructure based on Perl and Java that is required to build on these customized tools.

More recently I have been examining the problems associated with visualization of large plant pedigrees and addressing some of these with the development of visualization tools such as Helium.

The above video shows an example of visualization of a large barley pedigree in the Helium pedigree visualization application.

The database and visualization side of my work has led to my involvement in the Seeds of Discovery project in collaboration with CIMMYT in Mexico and DArT in Australia.

 

Germinate 3

Germinate is a generic plant genetic resources database and offers facilities to store both standard collection information and passport data along with more advanced data types such as phenotypic, genotypic and field trial data. Germinate was originally implemented in MySQL and Perl but is moving with version 3 to MySQL and Google Web Toolkit (GWT). Germinate is not a standalone desktop application and requires MySQL, Apache Tomcat and GWT to run. The usual use case would be installation on a Linux based server.

Currently there are Germinate installations for barley, wheat, potato, Lolium, Festuca, maize and pea although the generic nature of the system makes it suitable for storage of data from a wide variety of sources and species. We are currently developing Germinate to handle large scale trials data and data from high throughput genotpying experiments.
Germinate is being used to support work being carried out in a number of external projects including AGOUEB (Association Genetics of UK Elite Barley), IMPROMALT (Improving Malting Quality in Winter Barley) and Seeds of Discovery where we have implementations holding passport, genotypic and phenotypic data from the wheat and maize germplasm collections from CIMMYT in Mexico.

Other Databases

Germinate Pea
Pea database comprising accessions from the John Innes collection, one of the widest and most comprehensive sets of Psium germplasm worldwide. Aso includes Retrotransposon-Based Insertion Polymorphism (RBIP) marker data. 

Germinate Grasses
Database holding information on Lolium and Festuca accessions as well as genotypic data based on the DArT platform.

Commonwealth Potato Collection Database
This potato database contains passport and disease resistance data across the accessions contained within the Commonwealth potato collection at SCRI. This resource is based on the Germinate 2 platform.

AtNoPDB
The Arabidopsis Nucleolar Protein database (AtNoPDB) provides information on 217 Arabidopsis proteins in comparison to human and yeast proteins.

Wheat In-Situ Database
This resource was developed and implemented at SCRI to hold the data obtained from a joint BBSRC and Syngenta project for high-throughput wheat in situ hybridisation.

Plant snoRNA Database
This resource brings together information from three independant computer-assisted searches of the Arabidopsis genome for box C/D snoRNA genes and from studies of ncRNAs.

Areas of Expertise

  • Database design and implementation.
  • Web application and interface development.
  • Biological data visualization.
  • Large scale biological data handling and error checking.

Bibliography 


  • Email: info@hutton.ac.uk
  • Phone: +44 (0)844 928 5428
  • Craigiebuckler Aberdeen AB15 8QH Scotland
  • Invergowrie Dundee DD2 5DA Scotland
A Scottish charitable company limited by guarantee. Registered in Scotland No SC374831.
Registered office: The James Hutton Institute, Invergowrie Dundee DD2 5DA. Charity No SCO41796

Printed from /staff/paul-shaw on 01/06/16 04:29:21 AM

The James Hutton Research Institute is the result of the merger in April 2011 of MLURI and SCRI. This merger formed a new powerhouse for research into food, land use, and climate change.