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Network inference or reconstruction algorithms play an integral role in successfully analyzing and identifying causal relationships between omics hits for detecting dysregulated and altered signaling components in various contexts, encompassing disease states and drug perturbations. However, accurate representation of signaling networks and identification of context-specific interactions within sparse omics datasets in complex interactomes pose significant challenges in integrative approaches. To address these challenges, we present pyPARAGON (PAgeRAnk-flux on Graphlet-guided network for multi-Omic data integratioN), a novel tool that combines network propagation with graphlets. pyPARAGON enhances accuracy and minimizes the inclusion of nonspecific interactions in signaling networks by utilizing network rather than relying on pairwise connections among proteins. Through comprehensive evaluations on benchmark signaling pathways, we demonstrate that pyPARAGON outperforms state-of-the-art approaches in node propagation and edge inference. Furthermore, pyPARAGON exhibits promising performance in discovering cancer driver networks. Notably, we demonstrate its utility in network-based stratification of patient tumors by integrating phosphoproteomic data from 105 breast cancer tumors with the interactome and demonstrating tumor-specific signaling pathways. Overall, pyPARAGON is a novel tool for analyzing and integrating multi-omic data in the context of signaling networks. pyPARAGON is available at https://github.com/netlab-ku/pyPARAGON. [ABSTRACT FROM AUTHOR]

Being one of the countries with high solar irradiance levels, Turkey has a significant potential for hydrogen production from solar energy, which can play a crucial role in the country's transition from fossil fuels to renewable energy. This study offers a comprehensive analysis of solar energy systems producing hydrogen in Turkey with respect to energy and exergy efficiencies and hydrogen production rates. The systems that use not only solar energy, acquired through solar thermal collectors, photovoltaic, and photovoltaic/thermal panels, but also hybrid systems that integrate solar energy with various other renewable sources are examined. The findings show that the energy and exergy efficiencies of the systems vary within a wide range. The energy efficiency ranges from 3.44 % to 80 % and the exergy efficiency varies between 3.44 % and 93 %. Also, it was found that systems that use only solar energy via concentrating solar collectors and solar-biomass hybrid systems are the most efficient systems with respect to energy and exergy efficiencies and hydrogen production rates. Besides, photovoltaic panels have widespread and well-established use. Hence, these technologies are the most promising for future solar hydrogen production in Turkey. • PTCs, PDCs and HFCs are most analyzed solar technologies for hydrogen production. • Only-solar concentrating and solar-biomass systems are the most efficient systems. • Only-solar concentrating and solar-biomass systems produce more hydrogen. • There are high performing systems within each group of solar technology. [ABSTRACT FROM AUTHOR]

The intent of the present investigation is to conduct; experimentally, the effects of nanofluid of water/magnetite and flow channel arrangement on photovoltaic thermal (PVT) systems. Three different configurations of the collector in PVT were researched in various nanofluid's flow rate of M ˙ = 20.0 − 80.0 (k g / h r) , and nano concentration of φ = 0.0 − 2.0 %. The studied arrangements of flow channels in the collector are a sheet-and-plain serpentine tube (PVT-0S), a sheet-and-finned serpentine tube with four fins (PVT-4S) and a sheet-and-finned serpentine tube with eight fins (PVT-8S). The electrical efficiency is compared between the cited three cases and the PV panel without cooling system. The maximum energetic, exergetic and electrical performances were found at the flow rate of M ˙ = 80 (k g / h r) and nano concentration of φ = 2.0 %. It was observed that the PVT-8S system provides the most efficient configuration since the overall energy efficiency (η) in the PVT-8S system are 5.87 % , and 15.59 % higher than the PVT-4S, and PVT-0S systems. Further, the PVT-8S system demonstrated the maximum value of exergy efficiency (Γ = 14.51 %) compared to other studied systems. It was also shown that the electrical efficiency (Λ) augments significantly with the adding the cooling systems to the PV panel. The increase in the electrical efficiency was 12.06 % , 10.87 % , and 8.40 % for the PVT-8S, PVT-4S, and PVT-0S systems; respectively. • The maximum energetic performance is obtained at the flow rate, and volume fraction of 80 (kg/hr) and 2.0%. • The highest overall energy and exergy efficiencies were achieved for the PVT-8S system. • PVT-8S, PVT-4S, and PVT-0S have 12.06%, 10.87%, and 8.40% higher electrical efficiency than PV panel. [ABSTRACT FROM AUTHOR]