A collaborative environment for developing and validating predictive tools for protein biophysical characteristics |
| |
Authors: | Michael A Johnston Damien Farrell Jens Erik Nielsen |
| |
Institution: | (1) School of Biomolecular and Biomedical Science, Centre for Synthesis and Chemical Biology, UCD Conway Institute, University College Dublin, Belfield, Dublin 4, Ireland |
| |
Abstract: | The exchange of information between experimentalists and theoreticians is crucial to improving the predictive ability of theoretical
methods and hence our understanding of the related biology. However many barriers exist which prevent the flow of information
between the two disciplines. Enabling effective collaboration requires that experimentalists can easily apply computational
tools to their data, share their data with theoreticians, and that both the experimental data and computational results are
accessible to the wider community. We present a prototype collaborative environment for developing and validating predictive
tools for protein biophysical characteristics. The environment is built on two central components; a new python-based integration
module which allows theoreticians to provide and manage remote access to their programs; and PEATDB, a program for storing
and sharing experimental data from protein biophysical characterisation studies. We demonstrate our approach by integrating
PEATSA, a web-based service for predicting changes in protein biophysical characteristics, into PEATDB. Furthermore, we illustrate
how the resulting environment aids method development using the Potapov dataset of experimentally measured ΔΔGfold values, previously employed to validate and train protein stability prediction algorithms. |
| |
Keywords: | |
本文献已被 PubMed SpringerLink 等数据库收录! |
|