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Using PEAT to capture, share and analyze protein experimental data

Date:
October 22, 2010
Source:
UCD Conway Institute of Biomolecular & Biomedical Research
Summary:
Researchers in Ireland have created a novel application that not only facilitates the analysis of experimental data generated in the course of a research project but also ensures that this valuable data is available for future use.
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Researchers in Ireland's UCD Conway Institute led by Conway Fellow, Dr Jens Erik Nielsen have created a novel application that not only facilitates the analysis of experimental data generated in the course of a research project but also ensures that this valuable data is available for future use. The team described the application in an article published recently in the journal, Nucleic Acids Research.

PEAT (Protein Engineering Analysis Tool) is not simply another laboratory information management system, but has been designed to address specific tasks encountered in a typical protein engineering project while integrating data deposition in the process.

Proteins are often described as the building blocks within organisms given their central role in critical cell functions. When changes occur in the structure or function of proteins, diseases such as Alzheimer's or cancer can result. Consequently, a significant proportion of research efforts concentrate on dissecting, optimising or changing proteins in an effort to find new treatments for such diseases.

Vast amounts of data are generated annually through the protein engineering techniques used in the process of studying proteins. Although this valuable experimental data could be used in other research projects, there is no requirement to deposit it in a database before publishing and so it is unavailable for re-analysis or essentially 'lost' within the pages of a thesis or journal article.

Commenting on the benefits of PEAT, Dr Nielsen said, "The task of data capture and database deposition is often seen as a tedious and unrewarding process. PEAT incentivises data storage by integrating the process with the analysis tools in a single application. I hope that researchers will see the benefits of using PEAT so that we can create and share high quality datasets on the connections between protein sequence, structure and function."

PEAT is written in the python programming language and, although still under active development, has been road tested on several projects within Nielsen's laboratory, and has been used to establish several online databases. Additional functionality specific to particular research projects can be implemented with specifically written plug-ins that allow users to tailor the functionality of PEAT to specific experiments, proteins or scientific questions.


Story Source:

The above post is reprinted from materials provided by UCD Conway Institute of Biomolecular & Biomedical Research. Note: Materials may be edited for content and length.


Journal Reference:

  1. Damien Farrell, Fergal O’Meara, Michael Johnston, John Bradley, Chresten R. Søndergaard, Nikolaj Georgi, Helen Webb, Barbara Mary Tynan-Connolly, Una Bjarnadottir, Tommy Carstensen, Jens Erik Nielsen. Capturing, sharing and analysing biophysical data from protein engineering and protein characterization studies. Nucleic Acids Research, 2010; DOI: 10.1093/nar/gkq726

Cite This Page:

UCD Conway Institute of Biomolecular & Biomedical Research. "Using PEAT to capture, share and analyze protein experimental data." ScienceDaily. ScienceDaily, 22 October 2010. <www.sciencedaily.com/releases/2010/10/101020084231.htm>.
UCD Conway Institute of Biomolecular & Biomedical Research. (2010, October 22). Using PEAT to capture, share and analyze protein experimental data. ScienceDaily. Retrieved August 29, 2015 from www.sciencedaily.com/releases/2010/10/101020084231.htm
UCD Conway Institute of Biomolecular & Biomedical Research. "Using PEAT to capture, share and analyze protein experimental data." ScienceDaily. www.sciencedaily.com/releases/2010/10/101020084231.htm (accessed August 29, 2015).

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