In order to effectively use machine learning algorithms, e.g., neural networks, for the analysis of survival data, the correct treatment of censored data is crucial. The concordan...
This paper presents a biologically-inspired, hardware-realisable spiking neuron model, which we call the Temporal Noisy-Leaky Integrator (TNLI). The dynamic applications of the mo...
Chris Christodoulou, Guido Bugmann, Trevor G. Clar...
Our dynamic graph-based relational mining approach has been developed to learn structural patterns in biological networks as they change over time. The analysis of dynamic network...
Background: We present here the recent update of AMS algorithm for identification of post-translational modification (PTM) sites in proteins based only on sequence information, us...
Abstract--An Elman network (EN) can be viewed as a feedforward (FF) neural network with an additional set of inputs from the context layer (feedback from the hidden layer). Therefo...