In latest years, there has been an increasing attention to chemoinformatic and modeling methods enabling selectivity predictions for small molecules in case of same mechanism of action. Selectivity profiling of small molecules is emerging as one of the most expensive, though yet unmissable, task in drug discovery and cross-reactivity prediction as one of the most challenging chemoinformatic fie...

This paper proposes a modification to the restricted Boltzmann machine (RBM) learning algorithm to incorporate inductive biases. These latent activation biases are ideal solutions of the latent activity and may be designed either by modeling neural phenomenon or inductive principles of the task. In this paper, we design activation biases for sparseness and selectivity based on the activation di...

Auditory neurons in the inferior colliculus (IC) show remarkable selectively in that they can distinguish between complex sounds that have identical spectral energy but different temporal structure, such as frequency modulations (FMs) that sweep either upward or downward. Extracellular recordings show that blocking inhibition locally reduces or eliminates response selectivity, suggesting that s...

Many applications in auditory modeling require analysis filters that approximate the frequency selectivity given by psychophysical data, e.g. from masking experiments using narrow-band maskers. This frequency selectivity is largely determined by the spectral decomposition process inside the human cochlea. Currently used spectral decomposition schemes for masking modeling in audio coding general...

The application of membranes in various industries is one of the most urgent needs to reduce energy consumption and environmental pollutants as well as low investment costs in the process of separation. In this investigation, the optimization of effective parameters for separation of gas mixture of CH4, CO2, O2 and N2 is studied by modified poly(4-met...

Accurate modeling and design of protein-ligand interactions have broad applications in cell biology, synthetic biology and drug discovery but remain challenging without experimental protein structures. Here we developed an integrated protein-homology-modeling, ligand-docking protein-design approach that reconstructs protein-ligand binding sites from homolog protein structures in the presence of...

A computer modeling technique has been developed which allows for the prediction of chromatographic separation and stationary-phase selectivity. This technique enables development of application-specific gas chromatographic columns by allowing for the simultaneous optimization of physical dimensions, flow and temperature programs, and stationary-phase composition. Stationary-phase selectivity i...

Running average is a simple and effective background modeling method that generates adaptive background image for moving object detection. Fuzzy Running Average (FRA) improves the selectivity of Standard Running Average (SRA). However, its background restoration rate is slow. This leads to false object detection when a static object becomes dynamic. To overcome this problem, an Extended Fuzzy R...