Mathematical modeling of regulatory networks of intracellular processes – Aims and selected methods

Kardyńska, Małgorzata; Kogut, Daria; Pacholczyk, Marcin; Śmieja, Jarosław

doi:10.1016/j.csbj.2023.02.006

Cited by 7 publications

(5 citation statements)

References 143 publications

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“…Finally, the bioinformatics analysis showed us an exciting signature of genes and miRNAs. In this sense, since the discovery of mathematics, the human being has tried to find an explanation through numbers for our entire environment, and today thanks to the advancement of technology and, in this case of computing, it has become much easier to try to predict the behavior of biological systems with the help of diverse bioinformatics software and algorithms [ 32 ]. In this context, with the help of powerful bioinformatic tools, several studies have tried to predict different molecular pathways that are directly related lncRNAs, miRNAs, and genes, which have increased the knowledge about interactions between that kind of molecules [ 33 , 34 ].…”

Section: Discussionmentioning

confidence: 99%

Whole Blood Expression Levels of Long Noncoding RNAs: HOTAIRM1, GAS5, MZF1-AS1, and OIP5-AS1 as Biomarkers in Adolescents with Obesity-Related Asthma

Leija-Martínez

Guzmán-Martín

González-Ramírez

et al. 2023

IJMS

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Asthma is a heterogeneous entity encompassing distinct endotypes and varying phenotypes, characterized by common clinical manifestations, such as shortness of breath, wheezing, and variable airflow obstruction. Two major asthma endotypes based on molecular patterns are described: type 2 endotype (allergic-asthma) and T2 low endotype (obesity-related asthma). Long noncoding RNAs (lncRNAs) are transcripts of more than 200 nucleotides in length, currently involved in many diverse biological functions, such as chromatin remodeling, gene transcription, protein transport, and microRNA processing. Despite the efforts to accurately classify and discriminate all the asthma endotypes and phenotypes, if long noncoding RNAs could play a role as biomarkers in allergic asthmatic and adolescent obesity-related asthma, adolescents remain unknown. To compare expression levels of lncRNAs: HOTAIRM1, OIP5-AS1, MZF1-AS1, and GAS5 from whole blood of Healthy Adolescents (HA), Obese adolescents (O), allergic asthmatic adolescents (AA) and Obesity-related asthma adolescents (OA). We measured and compared expression levels from the whole blood of the groups mentioned above through RT-q-PCR. We found differentially expressed levels of these lncRNAs between the groups of interest. In addition, we found a discriminative value of previously mentioned lncRNAs between studied groups. Finally, we generated an interaction network through bioinformatics. Expression levels of OIP5-AS1, MZF1-AS1, HOTAIRM1, and GAS5 in whole blood from the healthy adolescent population, obese adolescents, allergic asthma adolescents, and obesity-related asthma adolescents are differently expressed. Moreover, these lncRNAs could act as molecular biomarkers that help to discriminate between all studied groups, probably through molecular mechanisms with several genes and miRNAs implicated.

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Section: Discussionmentioning

confidence: 99%

Whole Blood Expression Levels of Long Noncoding RNAs: HOTAIRM1, GAS5, MZF1-AS1, and OIP5-AS1 as Biomarkers in Adolescents with Obesity-Related Asthma

Leija-Martínez

Guzmán-Martín

González-Ramírez

et al. 2023

IJMS

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“…On the other hand, control engineering that tackles similar problems in technical field provides plentiful of solutions. Finding analogies between these fields should facilitate much faster progress in molecular biology and medicine, supporting analysis of experimental results, in silico analysis of biological hypotheses as well as experiment planning This is why employing engineering knowledge and methods becomes more and more important in supporting biological research [30], helping to investigate unknown mechanisms regulating responses to various stress factors, interactions between specific signaling pathways, or phenomena like cellular signal memory [31]. Moreover, engineering methods, such as sensitivity analysis, may facilitate discovery of molecular targets for new drugs [32], a process which requires mathematical modeling of regulatory networks, molecular dynamics modeling, artificial intelligence-based tools and IT hardware and software infrastructure (Fig.…”

Section: How Engineering Can Help In Gaining Biological Knowledge And...mentioning

confidence: 99%

An engineering perspective on transcription, translation and their regulation

Smieja

2024

Postepy Biochem

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Information coded in DNA is replicated, modified and transmitted from the origins of protein-based life. Analogies of these processes to information processing, transmission and storage in computer systems is straightforward and can be utilized both in analysis of biological data and in development of biologically based technical systems. Transcription and translation processes are regulated by extremely complex regulatory networks, providing control of cell growth, cell cycle and cellular responses to stress. As such, they constitute engineering control systems exerting their actions at many levels of time scale and spatial organization. This work presents an engineering perspective on DNA-related information processing and biochemical process control in living cells, followed by a review of two-way crosstalk between engineering and biology.

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“…Omics and image data, 84 HIF, 85 general intracellular, 86 NO, 87 metabolism 27 Intercellular Angiogenesis, 88,89 extracellular matrix remodeling 90 Physics/flow dynamics Pulmonary circulation (pulmonary hypertension [PH]), 91 cardiac hypertrophy, 92 neonatal PH, 93 ventricular mechanics 94 Prognosis Pulmonary system, 95 drug combinations cancer, 96 nanoparticle drug delivery cancer 97 Clinical trials In silico trials, 98 drug design 99 Mathematical model…”

Section: Intracellularmentioning

confidence: 99%

A perfectly imperfect engine: Utilizing the digital twin paradigm in pulmonary hypertension

Walker,

Moore,

Ataya

et al. 2024

Pulm. circ.

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Pulmonary hypertension (PH) is a severe medical condition with a number of treatment options, the majority of which are introduced without consideration of the underlying mechanisms driving it within an individual and thus a lack of tailored approach to treatment. The one exception is a patient presenting with apparent pulmonary arterial hypertension and shown to have vaso‐responsive disease, whose clinical course and prognosis is significantly improved by high dose calcium channel blockers. PH is however characterized by a relative abundance of available data from patient cohorts, ranging from molecular data characterizing gene and protein expression in different tissues to physiological data at the organ level and clinical information. Integrating available data with mechanistic information at the different scales into computational models suggests an approach to a more personalized treatment of the disease using model‐based optimization of interventions for individual patients. That is, constructing digital twins of the disease, customized to a patient, promises to be a key technology for personalized medicine, with the aim of optimizing use of existing treatments and developing novel interventions, such as new drugs. This article presents a perspective on this approach in the context of a review of existing computational models for different aspects of the disease, and it lays out a roadmap for a path to realizing it.

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Mathematical modeling of regulatory networks of intracellular processes – Aims and selected methods

Cited by 7 publications

References 143 publications

Whole Blood Expression Levels of Long Noncoding RNAs: HOTAIRM1, GAS5, MZF1-AS1, and OIP5-AS1 as Biomarkers in Adolescents with Obesity-Related Asthma

Whole Blood Expression Levels of Long Noncoding RNAs: HOTAIRM1, GAS5, MZF1-AS1, and OIP5-AS1 as Biomarkers in Adolescents with Obesity-Related Asthma

An engineering perspective on transcription, translation and their regulation

A perfectly imperfect engine: Utilizing the digital twin paradigm in pulmonary hypertension

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