This paper presents asymptotic stability criteria for fractional‐order gene regulatory networks (FOGRNs) with impulses, time delays, and two numerical cases to illustrate the applicability of the results. The established system's boundedness, ...

In environments that vary frequently and unpredictably, bet-hedgers can overtake the population. Diversifying bet-hedgers have a diverse set of offspring so that, no matter the conditions they find themselves in, at least some offspring will have high ...

Accurate prediction of gene regulation rules is important for understanding complex life processes. Existing computational algorithms designed for bulk transcriptome datasets typically require a large number of time points to infer gene regulatory ...

We present hybrid system based gene regulatory network models for lambda, HK022 and Mu bacteriophages and analysis of dynamics and possible stable behaviours of the modelled networks. Lambda phage model LPH2 is the result of further development of an ...

A simple population based Evolutionary Algorithm (EA) was used to evolve convolutional neural networks for solving an image classification problem (CIFAR10). Each member of the population was defined by a genome. This work proposes the construction of a ...

Causality draws the relationship between the cause and the effect among a pair of items. Causality inference in Gene Regulatory Networks (GRNs) is a challenging task due to the limits of appropriate data and large dataset size of real networks. Such an ...

The genome and interactome of Saccharomyces cerevisiae have been characterized extensively over the course of the past few decades. However, despite many insights gained over the years, both functional studies and evolutionary analyses continue to ...

Many methods aim to use data, especially data about gene expression based on high throughput genomic methods, to identify complicated regulatory relationships between genes. The authors employ a simple but powerful tool, called fuzzy cognitive maps (FCMs),...

In this paper, we introduce a method based on recommendation systems to predict the structure of Gene Regulatory Networks (GRNs) making use of data from multiple sources. Our method is based on collaborative filtering approach enhanced with multiple ...

Accurate reconstruction of gene regulatory networks from time-series gene expression data is a significant challenge for computer scientists. In this paper, we have proposed a genetic algorithm and flower pollination algorithm hybrid for the reverse ...

The questions about nature that we can address using digital evolution are constrained by the speed of our software and the level of abstraction used in our genetic representations. One subject that has been particularly challenging is the evolution of ...

Wireless sensor networks (WSNs) generally comprise a large number of tiny sensor nodes that perform network processing of the acquired data and then forwarding such data to the sink via multi‐hop paths. The sensor nodes are resource constrained in terms ...

The ability to rationally manipulate the transcriptional states of cells would be of great use in medicine and bioengineering. We have developed an algorithm, NetSurgeon, which uses genome wide gene-regulatory networks to identify interventions that ...

In many real applications such as bioinformatics and biological network analysis, it has always been an important, yet challenging, topic to accurately infer/reconstruct gene regulatory networks (GRNs) from microarray data, and efficiently identify ...

In this paper, we propose a novel ensemble Kalman filter based particle filter for gene regulatory networks (GRNs) analysis, which incorporates ensemble Kalman filter into particle filter. New particles generated by particle filter are sampled by ...

Prostate cancer is one of the most prevalent cancers in males in the United States and amongst the leading causes of cancer related deaths. A particularly virulent form of this disease is castration-resistant prostate cancer (CRPC), where patients no ...

Robust adaptation plays a key role in gene regulatory networks, and it is thought to be an important attribute for the organic or cells to survive in fluctuating conditions. In this paper, a simplified three-node enzyme network is modeled by the ...

Construction of gene regulatory network GRN is very important as it governs the expression levels of biomolecules in microarray data. In this article, we have developed GRNs by adaptive neural network ANN and self-organising map SOM approaches over ...

The inference of gene regulatory networks GRNs from expression profiles is still an important challenge in bioinformatics research. The main difficulty of this problem is associated to the huge number of genes and the small number of samples available, ...

RNA-Seq techniques generate hundreds of millions of short RNA reads using next-generation sequencing (NGS). These RNA reads can be mapped to reference genomes to investigate changes of gene expression but improved procedures for mining large RNA-Seq ...