After many months of hard work, the day is here! Our new paper on methods to predict 14-3-3-binding sites is out in Bioinformatics Journal. This project originated as a collaboration between the Barton Group and the MacKintosh Group on the quest for improving the quality of predictions on 14-3-3-binding sites.
This work was really exciting because put together nice science with nice technology. I really enjoyed learning a lot more about artificial neural networks and support vector machines. In addition to this, I had the chance to developed a webpage server enabling other researchers to use the new methods in a convenient way. The webserver was mainly developed in Python with Flask and is available at compbio.dundee.ac.uk/14-3-3-Pred
My paper on new methods to predict 14-3-3-binding phosphosites is out now! http://t.co/yMBMkzMQmm thanks @gjbarton and @CarolMacKintos1
— Fábio Madeira (@biomadeira) March 4, 2015The paper is open access and can be found at the reference below:
Fábio Madeira, Michele Tinti, Gavuthami Murugesan, Emily Berrett, Margaret Stafford, Rachel Toth, Christian Cole, Carol MacKintosh and Geoffrey J. Barton. 2015. 14-3-3-Pred: Improved methods to predict 14-3-3-binding phosphopeptides. Bioinformatics (Oxford). 2015 Mar 3; 2015:btv133.