Publications by authors named "Mohsen Riahi Manesh"
Article Synopsis
- Tumor microenvironments (TMEs) are complex ecosystems where cancer cells and immune cells interact, influencing cancer growth and treatment responses, but modeling tumor progression accurately remains a challenge.
- This study presents a framework that uses single-cell RNA sequencing data in a multilayer network model to explore molecular changes during glioma progression, effectively capturing the complexity of biological systems.
- Analysis of glioma stages revealed important ligand-receptor interactions and key genes in the Receptor Tyrosine Kinases (RTK) signaling pathway, which could predict progression with high accuracy, suggesting potential for improving prognosis and therapy strategies.
In diversity combining at the receiver, the output signal-to-noise ratio (SNR) is often maximized by using the maximal ratio combining (MRC) provided that the channel is perfectly estimated at the receiver. However, channel estimation is rarely perfect in practice, which results in deteriorating the system performance. In this paper, an imperialistic competitive algorithm (ICA) is proposed and compared with two other evolutionary based algorithms, namely, particle swarm optimization (PSO) and genetic algorithm (GA), for diversity combining of signals travelling across the imperfect channels.
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