Results 251 to 260 of about 234,524 (292)

Pathogenic Potential of <i>Erysipelothrix piscisicarius</i> in Pigs and Its Implications for Surveillance in Brazil. [PDF]

open access: yesTransbound Emerg Dis
Petri FM   +11 more
europepmc   +1 more source

Effect of medium composition on in vitro ovary culture of cucumber. [PDF]

open access: yesSci Rep
Nyirahabimana F   +3 more
europepmc   +1 more source

Defining postoperative spinal infections: navigating the inconsistencies in diagnostic definitions. [PDF]

open access: yesJ Bone Jt Infect
Alavi SMA   +7 more
europepmc   +1 more source

FIN-EGFRprint: a Finnish real-world study on treatments and outcomes in advanced NSCLC with common EGFR mutations. [PDF]

open access: yesActa Oncol
Knuuttila A   +7 more
europepmc   +1 more source
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Modelling Disease – Drug Networks with Petri Nets

2023 5th International Conference on Problems of Cybernetics and Informatics (PCI), 2023
Quantitative modelling of biological systems with Petri nets has undergone a renaissance over the past two decades. In spite of ever-growing numbers of models, it is still a question whether such models are biologically relevant. Despite the fact that most of the biological processes are mesoscopic in scale, the majority of models uses deterministic ...
openaire   +1 more source

An approach of disease-drug interaction model with Stochastic Petri Net

2017 Trends in Industrial Measurement and Automation (TIMA), 2017
From the past decades it is observed that Stochastic Petri Net (SPN) is a better tool for design and analysis of biological systems. The factor of Randomness and Unclearness in the design of biological system paved the way for the use of SPN. A Generic human immunity system modeled as a SIR(Susceptible Infected and Recovered) model is considered and ...
K Latha, K Selvakumar
exaly   +2 more sources

Petri net models and non linear genetic diseases

2010 IEEE Fifth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA), 2010
Understanding how an individual genetic make-up influences their risk of diseases, is a problem of paramount importance. Although machine-learning techniques are unable to uncover the relationships between genotype and disease, we can still build the best biochemical model automatically with the help of methods that identify the DNA sequence variations
P. Persis Glory   +2 more
openaire   +1 more source

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