scholarly journals Identifying the Salient Genes in Microarray Data: A Novel Game Theoretic Model for the Co-Expression Network

Diagnostics ◽  
2020 ◽  
Vol 10 (8) ◽  
pp. 586
Author(s):  
Papori Neog Bora ◽  
Vishwa Jyoti Baruah ◽  
Surajit Borkotokey ◽  
Loyimee Gogoi ◽  
Priyakshi Mahanta ◽  
...  
Keyword(s):  
Gene Expression ◽  
Genetic Diseases ◽  
System Level ◽  
Theoretic Model ◽  
Cancer Dataset ◽  
Network Games ◽  
Diagnosis And Prognosis ◽  
Network Game ◽  
Game Theoretic ◽  
Relevance Index

Microarray techniques are used to generate a large amount of information on gene expression. This information can be statistically processed and analyzed to identify the genes useful for the diagnosis and prognosis of genetic diseases. Game theoretic tools are applied to analyze the gene expression data. Gene co-expression networks are increasingly used to explore the system-level functionality of genes, where the roles of the genes in building networks in addition to their independent activities are also considered. In this paper, we develop a novel microarray network game by constructing a gene co-expression network and defining a game on this network. The notion of the Link Relevance Index (LRI) for this network game is introduced and characterized. The LRI successfully identifies the relevant cancer biomarkers. It also enables identifying salient genes in the colon cancer dataset. Network games can more accurately describe the interactions among genes as their basic premises are to consider the interactions among players prescribed by a network structure. LRI presents a tool to identify the underlying salient genes involved in cancer or other metabolic syndromes.

scholarly journals A network approach to rebel fighting durations in civil wars

2019 ◽  
Author(s):  
Nils W Metternich ◽  
Julian Wucherpfennig
Keyword(s):  
Civil Wars ◽  
Strategic Behavior ◽  
Model Fit ◽  
Conflict Behavior ◽  
Theoretic Model ◽  
Empirical Measures ◽  
Statistical Framework ◽  
Network Game ◽  
Game Theoretic ◽  
Game Theoretic Model

Recent research on multi-actor civil wars highlights that rebel organizations condition their conflict behavior on that of other rebel organizations, with competition and free-riding constituting the core theoretical mechanisms. We provide a new actor-centric approach to explicitly model strategic interdependence in multi-actor civil wars. We argue that competitive dynamics dominate strategic behavior between rebel organizations, but these can be offset by incentives to free-ride in cases where the underlying incompatibility displays public good characteristics. Based on a network game theoretic model, we derive a statistical framework that allows for a direct test of strategic interdependence. We find that the estimated duration interdependence is positive, that is weaker in secessionist conflicts, and that modeling this interdependence explicitly outweighs existing empirical measures of interdependence (e.g. number of organizations). Finally, we demonstrate that the model fit of rebel organizations' fighting durations can be improved by taking strategic interdependence into account.

Stability in the informal value transfer systems: norms of trust or institutions of control?

2017 ◽  
pp. 120-130
Author(s):  
A. Lyasko
Keyword(s):  
Social Control ◽  
Institutional Economics ◽  
Theoretic Model ◽  
Transfer System ◽  
Value Transfer ◽  
Partner Interaction ◽  
Game Theoretic ◽  
Game Theoretic Model ◽  
Informal Value Transfer System

Informal financial operations exist in the shadow of official regulation and cannot be protected by the formal legal instruments, therefore raising concerns about the enforcement of obligations taken by their participants. This paper analyzes two alternative types of auxiliary institutions, which can coordinate expectations of the members of informal value transfer systems, namely attitudes of trust and norms of social control. It offers some preliminary approaches to creating a game-theoretic model of partner interaction in the informal value transfer system. It also sheds light on the perspectives of further studies in this area of institutional economics.

Hollywood’s Movie Production Companies in Game Theoretic Model

2020 ◽  
Author(s):  
Nargiz Mammadova ◽  
Aygun Malikova ◽  
Arzu Heydarova
Keyword(s):  
Theoretic Model ◽  
Game Theoretic ◽  
Game Theoretic Model

Digital Authoritarianism and the Future of Human Rights

2021 ◽  
pp. 1-27
Author(s):  
Tiberiu Dragu ◽  
Yonatan Lupu
Keyword(s):  
Human Rights ◽  
New Technologies ◽  
Theoretic Model ◽  
Human Rights Abuses ◽  
Human Rights Regime ◽  
Wide Range ◽  
The Future ◽  
Technological Developments ◽  
Game Theoretic ◽  
Strategic Context

Abstract How will advances in digital technology affect the future of human rights and authoritarian rule? Media figures, public intellectuals, and scholars have debated this relationship for decades, with some arguing that new technologies facilitate mobilization against the state and others countering that the same technologies allow authoritarians to strengthen their grip on power. We address this issue by analyzing the first game-theoretic model that accounts for the dual effects of technology within the strategic context of preventive repression. Our game-theoretical analysis suggests that technological developments may not be detrimental to authoritarian control and may, in fact, strengthen authoritarian control by facilitating a wide range of human rights abuses. We show that technological innovation leads to greater levels of abuses to prevent opposition groups from mobilizing and increases the likelihood that authoritarians will succeed in preventing such mobilization. These results have broad implications for the human rights regime, democratization efforts, and the interpretation of recent declines in violent human rights abuses.

scholarly journals CFTR Cooperative Cis-Regulatory Elements in Intestinal Cells

2021 ◽  
Vol 22 (5) ◽  
pp. 2599
Author(s):  
Mégane Collobert ◽  
Ozvan Bocher ◽  
Anaïs Le Nabec ◽  
Emmanuelle Génin ◽  
Claude Férec ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cystic Fibrosis ◽  
Gene Regulation ◽  
Genetic Diseases ◽  
Regulatory Elements ◽  
Cftr Gene ◽  
Intestinal Cells ◽  
Cooperative Effects ◽  
Cis Acting ◽  
Study Techniques

About 8% of the human genome is covered with candidate cis-regulatory elements (cCREs). Disruptions of CREs, described as “cis-ruptions” have been identified as being involved in various genetic diseases. Thanks to the development of chromatin conformation study techniques, several long-range cystic fibrosis transmembrane conductance regulator (CFTR) regulatory elements were identified, but the regulatory mechanisms of the CFTR gene have yet to be fully elucidated. The aim of this work is to improve our knowledge of the CFTR gene regulation, and to identity factors that could impact the CFTR gene expression, and potentially account for the variability of the clinical presentation of cystic fibrosis as well as CFTR-related disorders. Here, we apply the robust GWAS3D score to determine which of the CFTR introns could be involved in gene regulation. This approach highlights four particular CFTR introns of interest. Using reporter gene constructs in intestinal cells, we show that two new introns display strong cooperative effects in intestinal cells. Chromatin immunoprecipitation analyses further demonstrate fixation of transcription factors network. These results provide new insights into our understanding of the CFTR gene regulation and allow us to suggest a 3D CFTR locus structure in intestinal cells. A better understand of regulation mechanisms of the CFTR gene could elucidate cases of patients where the phenotype is not yet explained by the genotype. This would thus help in better diagnosis and therefore better management. These cis-acting regions may be a therapeutic challenge that could lead to the development of specific molecules capable of modulating gene expression in the future.

scholarly journals Promoter Methylation of PRKCB, ADAMTS12, and NAALAD2 Is Specific to Prostate Cancer and Predicts Biochemical Disease Recurrence

2021 ◽  
Vol 22 (11) ◽  
pp. 6091
Author(s):  
Kristina Daniunaite ◽  
Arnas Bakavicius ◽  
Kristina Zukauskaite ◽  
Ieva Rauluseviciute ◽  
Juozas Rimantas Lazutka ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Clinical Practice ◽  
Promoter Methylation ◽  
Disease Recurrence ◽  
The Cancer Genome Atlas ◽  
Cancer Dataset ◽  
Protein Coding ◽  
Diagnosis And Prognosis ◽  
Genome Wide ◽  
Cancer Genome Atlas

The molecular diversity of prostate cancer (PCa) has been demonstrated by recent genome-wide studies, proposing a significant number of different molecular markers. However, only a few of them have been transferred into clinical practice so far. The present study aimed to identify and validate novel DNA methylation biomarkers for PCa diagnosis and prognosis. Microarray-based methylome data of well-characterized cancerous and noncancerous prostate tissue (NPT) pairs was used for the initial screening. Ten protein-coding genes were selected for validation in a set of 151 PCa, 51 NPT, as well as 17 benign prostatic hyperplasia samples. The Prostate Cancer Dataset (PRAD) of The Cancer Genome Atlas (TCGA) was utilized for independent validation of our findings. Methylation frequencies of ADAMTS12, CCDC181, FILIP1L, NAALAD2, PRKCB, and ZMIZ1 were up to 91% in our study. PCa specific methylation of ADAMTS12, CCDC181, NAALAD2, and PRKCB was demonstrated by qualitative and quantitative means (all p < 0.05). In agreement with PRAD, promoter methylation of these four genes was associated with the transcript down-regulation in the Lithuanian cohort (all p < 0.05). Methylation of ADAMTS12, NAALAD2, and PRKCB was independently predictive for biochemical disease recurrence, while NAALAD2 and PRKCB increased the prognostic power of multivariate models (all p < 0.01). The present study identified methylation of ADAMTS12, NAALAD2, and PRKCB as novel diagnostic and prognostic PCa biomarkers that might guide treatment decisions in clinical practice.

Augmenting Employees’ Efforts in Innovation

2021 ◽  
pp. 097674792198917
Author(s):  
Nikita Jain
Keyword(s):  
Theoretic Model ◽  
Wrongful Discharge ◽  
Equilibrium Level ◽  
Game Theoretic ◽  
Game Theoretic Model ◽  
The Impact

Strong labour laws play a major role in motivating innovation among employees. It has been found in the literature that stringency of labour laws is positively linked with employees’ efforts in innovation, in particular, wrongful discharge laws (WDL). However, employees may also bring nuisance suits against employers. Usually, the result of these suits is that both parties settle with each other. Thus, even if employees are justly dismissed, they may be able to bring nuisance suits against employers and gain a settlement amount. This article investigates how the possibility of nuisance suits affects the impact of WDL on employees’ efforts in innovation. In this respect, a game-theoretic model is developed in the article to find the equilibrium level of employees’ efforts in the presence of nuisance suits, where there is a possibility of employees getting discharged from the firm. I find that if nuisance suits are a possibility, the stringency of WDL has no impact on employees’ efforts if defence cost of the firm is low; but for higher defence costs, WDL affects employees’ efforts. The efforts exerted by an employee are found to be weakly increasing in the defence costs of the firm.

scholarly journals Estimating the predictive power of silent mutations on cancer classification and prognosis

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Tal Gutman ◽  
Guy Goren ◽  
Omri Efroni ◽  
Tamir Tuller
Keyword(s):  
Gene Expression ◽  
Predictive Power ◽  
Predictive Ability ◽  
Cancer Classification ◽  
Silent Mutation ◽  
Cancer Type ◽  
Coding Region ◽  
Probability Of Survival ◽  
Diagnosis And Prognosis ◽  
Cancer Types

AbstractIn recent years it has been shown that silent mutations, in and out of the coding region, can affect gene expression and may be related to tumorigenesis and cancer cell fitness. However, the predictive ability of these mutations for cancer type diagnosis and prognosis has not been evaluated yet. In the current study, based on the analysis of 9,915 cancer genomes and approximately three million mutations, we provide a comprehensive quantitative evaluation of the predictive power of various types of silent and non-silent mutations over cancer classification and prognosis. The results indicate that silent-mutation models outperform the equivalent null models in classifying all examined cancer types and in estimating the probability of survival 10 years after the initial diagnosis. Additionally, combining both non-silent and silent mutations achieved the best classification results for 68% of the cancer types and the best survival estimation results for up to nine years after the diagnosis. Thus, silent mutations hold considerable predictive power over both cancer classification and prognosis, most likely due to their effect on gene expression. It is highly advised that silent mutations are integrated in cancer research in order to unravel the full genomic landscape of cancer and its ramifications on cancer fitness.

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