TY - JOUR A2 - Efe, Mehmet Onder AU - Yadav, Sarthak AU - Gupta, Manoj AU - Bist, Ankur Singh PY - 2018 DA - 2018/03/20 TI - Prediction of Ubiquitination Sites Using UbiNets SP - 5125103 VL - 2018 AB - Ubiquitination controls the activity of various proteins and belongs to posttranslational modification. Various machine learning techniques are taken for prediction of ubiquitination sites in protein sequences. The paper proposes a new MLP architecture, named UbiNets, which is based on Densely Connected Convolutional Neural Networks (DenseNet). Computational machine learning techniques, such as Random Forest Classifier, Gradient Boosting Machines, and Multilayer Perceptrons (MLP), are taken for analysis. The main target of this paper is to explore the significance of deep learning techniques for the prediction of ubiquitination sites in protein sequences. Furthermore, the results obtained show that the newly proposed model provides significant accuracy. Satisfactory experimental results show the efficiency of proposed method for the prediction of ubiquitination sites in protein sequences. Further, it has been recommended that this method can be used to sort out real time problems in concerned domain. SN - 1687-7101 UR - https://doi.org/10.1155/2018/5125103 DO - 10.1155/2018/5125103 JF - Advances in Fuzzy Systems PB - Hindawi KW - ER -