Background: Current scoring functions are not very successful in protein-ligand binding affinity prediction albeit their popularity in structure-based drug designs. Here, we propo...
In this paper we present the Dynamic Grow-Shrink Inference-based Markov network learning algorithm (abbreviated DGSIMN), which improves on GSIMN, the state-ofthe-art algorithm for...
In the foreseeable future, software testing will remain one of the best tools we have at our disposal to ensure software dependability. Empirical studies are crucial to software t...
Abstract-- In this paper a novel pulse sequence testing methodology is presented [22] as an alternative to Time Domain Reflectometry (TDR) for transmission line health condition mo...
Background: Hidden Markov Models (HMMs) provide an excellent means for structure identification and feature extraction on stochastic sequential data. An HMM-with-Duration (HMMwD) ...