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1.
Bioinformatics ; 38(19): 4652-4653, 2022 09 30.
Artigo em Inglês | MEDLINE | ID: mdl-35976128

RESUMO

MOTIVATION: The first and necessary step in systems approach to study biological phenomena is building a formal model. One of the possibilities is to construct a model based on Petri nets. They have an intuitive graphical representation on one hand, and on the other, can be analyzed using formal mathematical methods. Finding homologies or conserved processes playing important roles in various biological systems can be done by comparing models. The ones expressed as Petri nets are especially well-suited for such a comparison, but there is a lack of software tools for this task. RESULTS: To resolve this problem, a new analytical tool has been implemented in Holmes application and described in this article. It offers four different comparison methods, i.e. the ones based on t-invariants, decomposition, graphlets and branching vertices. AVAILABILITY AND IMPLEMENTATION: Available at http://www.cs.put.poznan.pl/mradom/Holmes/holmes.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.


Assuntos
Modelos Biológicos , Software , Simulação por Computador
2.
Int J Mol Sci ; 22(19)2021 Sep 29.
Artigo em Inglês | MEDLINE | ID: mdl-34638859

RESUMO

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), responsible for the coronavirus disease of 2019 (COVID-19) pandemic, has affected and continues to affect millions of people across the world. Patients with essential arterial hypertension and renal complications are at particular risk of the fatal course of this infection. In our study, we have modeled the selected processes in a patient with essential hypertension and chronic kidney disease (CKD) suffering from COVID-19, emphasizing the function of the renin-angiotensin-aldosterone (RAA) system. The model has been built in the language of Petri nets theory. Using the systems approach, we have analyzed how COVID-19 may affect the studied organism, and we have checked whether the administration of selected anti-hypertensive drugs (angiotensin-converting enzyme inhibitors (ACEIs) and/or angiotensin receptor blockers (ARBs)) may impact the severity of the infection. Besides, we have assessed whether these drugs effectively lower blood pressure in the case of SARS-CoV-2 infection affecting essential hypertensive patients. Our research has shown that neither the ACEIs nor the ARBs worsens the course infection. However, when assessing the treatment of hypertension in the active SARS-CoV-2 infection, we have observed that ARBs might not effectively reduce blood pressure; they may even have the slightly opposite effect. On the other hand, we have confirmed the effectiveness of arterial hypertension treatment in patients receiving ACEIs. Moreover, we have found that the simultaneous use of ARBs and ACEIs averages the effects of taking both drugs, thus leading to only a slight decrease in blood pressure. We are a way from suggesting that ARBs in all hypertensive patients with COVID-19 are ineffective, but we have shown that research in this area should still be continued.


Assuntos
COVID-19/complicações , Hipertensão Essencial/complicações , Insuficiência Renal Crônica/complicações , COVID-19/metabolismo , COVID-19/fisiopatologia , Simulação por Computador , Hipertensão Essencial/metabolismo , Hipertensão Essencial/fisiopatologia , Humanos , Modelos Biológicos , Insuficiência Renal Crônica/metabolismo , Insuficiência Renal Crônica/fisiopatologia , Sistema Renina-Angiotensina , SARS-CoV-2/isolamento & purificação , SARS-CoV-2/fisiologia
3.
Bioinformatics ; 33(23): 3822-3823, 2017 Dec 01.
Artigo em Inglês | MEDLINE | ID: mdl-28961696

RESUMO

SUMMARY: Model development and its analysis is a fundamental step in systems biology. The theory of Petri nets offers a tool for such a task. Since the rapid development of computer science, a variety of tools for Petri nets emerged, offering various analytical algorithms. From this follows a problem of using different programs to analyse a single model. Many file formats and different representations of results make the analysis much harder. Especially for larger nets the ability to visualize the results in a proper form provides a huge help in the understanding of their significance. We present a new tool for Petri nets development and analysis called Holmes. Our program contains algorithms for model analysis based on different types of Petri nets, e.g. invariant generator, Maximum Common Transitions (MCT) sets and cluster modules, simulation algorithms or knockout analysis tools. A very important feature is the ability to visualize the results of almost all analytical modules. The integration of such modules into one graphical environment allows a researcher to fully devote his or her time to the model building and analysis. AVAILABILITY AND IMPLEMENTATION: Available at http://www.cs.put.poznan.pl/mradom/Holmes/holmes.html. CONTACT: piotr@cs.put.poznan.pl.


Assuntos
Biologia Computacional/métodos , Simulação por Computador , Modelos Biológicos , Software , Biologia de Sistemas , Algoritmos
4.
Sci Rep ; 12(1): 20942, 2022 12 04.
Artigo em Inglês | MEDLINE | ID: mdl-36464715

RESUMO

Capability to compare biological models is a crucial step needed in an analysis of complex organisms. Petri nets as a popular modelling technique, needs a possibility to determine the degree of structural similarities (e.g., comparison of metabolic or signaling pathways). However, existing comparison methods use matching invariants approach for establishing a degree of similarity, and because of that are vulnerable to the state explosion problem which may appear during calculation of a minimal invariants set. Its occurrence will block usage of existing methods. To find an alternative for this situation, we decided to adapt and tests in a Petri net environment a method based on finding a distribution of graphlets. First, we focused on adapting the original graphlets for notation of bipartite, directed graphs. As a result, 151 new graphlets with 592 orbits were created. The next step focused on evaluating a performance of the popular Graphlet Degree Distribution Agreement (GDDA) metric in the new environment. To do that, we decided to use randomly generated networks that share typical characteristics of biological models represented in Petri nets. Our results confirmed the usefulness of graphlets and GDDA in Petri net comparison and discovered its limitations.


Assuntos
Modelos Biológicos , Receptores Proteína Tirosina Quinases
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