A5103111715- Gene Regulatory Network Analysis
- Computational Drug Discovery Methods
- Bioinformatics and Genomic Networks
- Sensor Technology and Measurement Systems
- Pesticide and Herbicide Environmental Studies
- Hearing Loss and Rehabilitation
- Cholinesterase and Neurodegenerative Diseases
- Speech and Audio Processing
- Blind Source Separation Techniques
- Gene expression and cancer classification
- Advanced Adaptive Filtering Techniques
- Innovation Policy and R&D
- Protein Degradation and Inhibitors
- Advancements in PLL and VCO Technologies
- Advanced Scientific Research Methods
- Music Technology and Sound Studies
- COVID-19 Clinical Research Studies
- Engine and Fuel Emissions
- Reliability and Maintenance Optimization
- Nutrition, Genetics, and Disease
- Freezing and Crystallization Processes
- Analog and Mixed-Signal Circuit Design
- Renewable energy and sustainable power systems
- SARS-CoV-2 and COVID-19 Research
- Smart Grid Energy Management
Technical University of Moldova
2023
Åbo Akademi University
2018-2022
Technical University of Cluj-Napoca
2006-2008
To better understand the potential of drug repurposing in COVID-19, we analyzed control strategies over essential host factors for SARS-CoV-2 infection. We constructed comprehensive directed protein-protein interaction (PPI) networks integrating top-ranked factors, target proteins and PPI data. to identify targets combinations thereof that offer efficient factors. validated our findings against clinical studies data bioinformatics studies. Our method offers a new insight into molecular...
Control theory has seen recently impactful applications in network science, especially connections with medicine. A key topic of research is that finding minimal external interventions offer control over the dynamics a given network, problem known as controllability. We propose this article new solution for based on genetic algorithms. tailor our computational drug repurposing, seeking to maximize its use FDA-approved targets disease-specific protein-protein interaction network. demonstrate...
There is an increasing amount of data coming from genome-wide studies identifying disease-specific survivability-essential proteins and host factors critical to a cell becoming infected. Targeting such has strong potential for targeted, precision therapies. Typically however, too few them are drug targetable. An alternative approach influence through targetable upstream them. Structural target network controllability suitable solution this problem. It aims discover source nodes (e.g....
The paper considers two efficient improved artificial reverberation algorithms built with an early Schroeder's and a late reverberator: modified or absorbent all-pass. Both of them simulate the behavior real concert hall by taking into account variation frequency time. Several can be found in literature, but very few design performance analysis hints are given. Our includes detailed reverberators, simulations run for each algorithm, acoustic parameters computed objective is carried out
The paper presents the structure and performance of signal processing algorithms that simulate natural room reverberation. It deals with three digital complete artificial reverberators, built up Schroeder's early reverberator a late all-pass filters: Schroeder's, Gardner's or absorbent reverberator. For each presented reverberation acoustic parameters are computed compared those concert hall.
Control theory has seen recently impactful applications in network science, especially connections with medicine. A key topic of research is that finding minimal external interventions offer control over the dynamics a given network, problem known as controllability. We propose this article new solution for based on genetic algorithms. tailor our computational drug repurposing, seeking to maximise its use FDA-approved targets disease-specific protein-protein interaction network. show how...
In this paper the low-IF receiver architecture, image interference due to IF domain, phenomena also referred as I/Q imbalance and a modification for blind source separation algorithm rejection are presented. The modified considers all received samples of signal estimation parameters. resulting filter's major advantage is single clock domain implementation at cost power consumption increase. A Simulink model was created check availability enhanced algorithm, its performance measured compared...
We created fast and precise behavioral blocks used for the measurement of power, average root mean square values in electronic circuits. The obtained results are better than ones offered by Pspice functions. method was tested on some filters illustrated DC-DC converters, where switch period is /spl mu/seconds it hard to obtain accurate data. signals can be seen through an adjustable window.
We discuss in this survey several network modeling methods and their applicability to precision medicine. review centrality (degree centrality, closeness eccentricity betweenness eigenvector-based prestige) two systems controllability (minimum dominating sets structural controllability). demonstrate medicine on three multiple myeloma patient disease networks. Each consists of protein-protein interactions built around a specific patient's mutated genes, the targets drugs used standard care...
The PSpice functions used for measuring the power, average and root mean square are not accurate enough because of using specific techniques like products or filters. We created fast precise specialised behavioural blocks that obtain values signals by applying an integral relation. computation is done after transitory regime finished so constant easy to be read. method was measurements in DC-DC converters, where switching period very small (10-20 μseconds).
We discuss in this chapter several network modelling methods and their applicability to precision medicine. review centrality (degree centrality, closeness eccentricity betweenness eigenvector-based prestige) two systems controllability (minimum dominating sets structural controllability). demonstrate medicine on three multiple myeloma patient disease networks. Each consists of protein–protein interactions (PPI) built around a specific patient's mutated genes, the targets drugs used standard...
Abstract Control theory has seen recently impactful applications in network science, especially connections with medicine. A key topic of research is that finding minimal external interventions offer control over the dynamics a given network, problem known as controllability. We propose this article new solution for based on genetic algorithms. tailor our computational drug repurposing, seeking to maximize its use FDA-approved targets disease-specific protein-protein interaction network....
The aim of this work is to estimate the influence random factors on operational reliability electricity supply networks. In order achieve proposed aim, interruptions in operation, caused by influencing factors, which occurred randomly process operation examined power grids were recorded and processed. Specific selected as object research, because at present they occur frequently interrupt unpredictably, essentially affecting consumers causing them significant harm. main results research...
The aim of this work consists in increasing the efficiency drying process seeded fruit products with application microwave tunnel treatment. To reach proposed aim, an experimental electrical installation has been designed, developed, tested, optimized and implemented, applying treatment process. Seeded general have selected as object research, because their is difficult, due to occurrence many adverse effects heat process, they are great interest consumers companies processing marketing...
Recent research has revealed new and unexpected applications of network control science within biomedicine, pharmacology, medical therapeutics. These insights generated in turn a rediscovery some old, unresolved algorithmic problems. One these problems is the Structural Target Control optimization problem, known previous literature also as Output Controllability which defined follows. Given directed target subset nodes, task to select small (or smallest) set nodes from can be independently...
Recent research has revealed new and unexpected applications of network control science within biomedicine, pharmacology, medical therapeutics. These insights generated in turn a rediscovery some old, unresolved algorithmic problems. One these problems is the Structural Target Control optimization problem, known previous literature also as Output Controllability which defined follows. Given directed target subset nodes, task to select small (or smallest) set nodes from can be independently...
To better understand the potential of drug repurposing in COVID-19, we analyzed control strategies over essential host factors for SARS-CoV-2 infection. We constructed comprehensive directed protein-protein interaction networks integrating top ranked factors, target proteins, and data. to identify targets combinations thereof that offer efficient factors. validated our findings against clinical studies data bioinformatics studies. Our method offers a new insight into molecular details...