University of Antwerp
Abstract traineeship advanced bachelor of bioinformatics 2017-2018: Development of an immunologic affinity prediction webtool
The current T cell epitope prediction tools typically focus on the prediction of peptide binding and presentation by molecules located on the surface of antigen-presenting cells (major histocompatibility complex molecules). These tools are capable of accurately performing these predictions. But what is not included in these tools is the prediction of peptide-MHC complex by T cell receptors (TCR). The ADReM Data lab is currently developing a classification model to predict recognition of a peptide by a TCR, based on random forest classifiers.
Also in development is a webtool called TCRex which is able to process input data based on these classifiers. With TCRex, it is possible to analyse TCR (CDR3) sequence data against a number of selected epitopes and predict the probability of an epitope binding with that given sequence. Also, the user can train and test a new classifier with the user’s own train and test data.
The TCRex webtool is developed in Django Web Development framework. Django is an open source, high-level Python Web framework based on the Model-view-controller-model. It is build by experienced developers and takes care of much of the hassle of web development, so it allows you to rapidly develop a web application “without the need of reinventing the wheel” [djangoproject.com, 2005].