Neural-like P systems with plasmids (NP P systems, in short) are a kind of distributed and parallel computing systems inspired by the activity that bacteria process DNA such as plasmids. An important biological fact is that one or more pili have exis...
Memristive technologies are attractive due to their non-volatility, high-density, low-power and compatibility with CMOS. For memristive devices, a model corresponding to practical behavioral characteristics is highly favorable for the realization of ...
Asynchronous spiking neural P systems with rules on synapses (ARSSN P systems) are a class of computation models, where spiking rules are placed on synapses. In this work, we investigate the computation power of ARSSN P systems working in the rule sy...
The neurotransmitter is a chemical substance that transmits information between neurons. Its metabolic process includes four links: synthesis, storage, release and inactivation. As one of the important chemical components of neurotransmitters, acetyl...
An accurate estimation of glomerular filtration rate (GFR) is clinically crucial for kidney disease diagnosis and predicting the prognosis of chronic kidney disease (CKD). Machine learning methodologies such as deep neural networks provide a potentia...
The unconventional nature of molecular communication necessitates contributions from a host of scientific fields making the simulator design for such systems to be quite challenging. The nervous system is one of the largest and most important nanonet...
In this paper, we focus on the cluster synchronization of reaction-diffusion genetic regulatory networks (RDGRNs) with time-varying delays, where the state of the system is not only time-dependent but also spatially-dependent due to the presence of t...
This work presents a large-scale three-fold annotated, low-cost microscopy image dataset of potato tubers for plant cell analysis in deep learning (DL) framework which has huge potential in the advancement of plant cell biology research. Indeed, low-...
A reconfigurable biosensor with different spectral sensitivities could provide new opportunities to increase the label-free selectivity and sensitivity for biomolecules. Here, we propose and numerically demonstrate a phase change chalcogenide materia...
The protein fold recognition is one of the important tasks of structural biology, which helps in addressing further challenges like predicting the protein tertiary structures and its functions. Many machine learning works are published to identify th...