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Papers by Maryam Shahdoust

Research paper thumbnail of wpLogicNet: logic gate and structure inference in gene regulatory networks

Bioinformatics

MotivationThe gene regulatory process resembles a logic system in which a target gene is regulate... more MotivationThe gene regulatory process resembles a logic system in which a target gene is regulated by a logic gate among its regulators. While various computational techniques are developed for a gene regulatory network (GRN) reconstruction, the study of logical relationships has received little attention. Here, we propose a novel tool called wpLogicNet that simultaneously infers both the directed GRN structures and logic gates among genes or transcription factors (TFs) that regulate their target genes, based on continuous steady-state gene expressions.ResultswpLogicNet proposes a framework to infer the logic gates among any number of regulators, with a low time-complexity. This distinguishes wpLogicNet from the existing logic-based models that are limited to inferring the gate between two genes or TFs. Our method applies a Bayesian mixture model to estimate the likelihood of the target gene profile and to infer the logic gate a posteriori. Furthermore, in structure-aware mode, wpLo...

Research paper thumbnail of Evaluation of Toxoplasma gondii infection in western Iran: seroepidemiology and risk factors analysis

Tropical Medicine and Health, 2020

Background Toxoplasmosis is a parasitic infectious disease, and Toxoplasma gondii is the causativ... more Background Toxoplasmosis is a parasitic infectious disease, and Toxoplasma gondii is the causative factor of this intracellular protozoan disease. Due to the lack of information about the rate of T. gondii in general papulation of Markazi Province in Iran, the current study was conducted to determine the prevalence of toxoplasmosis and the related risk factor analysis in the general population of Markazi Province. Methods This cross-sectional study was performed within 6 months on individuals who were referred to diagnostic laboratories in Markazi Province. The demographic and background information of the subjects were collected using a questionnaire. Three milliliters of blood samples was collected from the participants under sterile conditions. The sera were separated and evaluated for levels of anti-Toxoplasma IgG antibody using a commercial enzyme-linked immunosorbent assay (ELISA) method. The collected data were analyzed by the SPSS software using descriptive statistics and ch...

Research paper thumbnail of Hepatogenesis and hepatocarcinogenesis: Alignment of the main signaling pathways

Journal of Cellular Physiology

Research paper thumbnail of Competitive exclusion during co-infection as a strategy to prevent the spread of a virus: A computational perspective

PLOS ONE, 2021

Inspired by the competition exclusion principle, this work aims at providing a computational fram... more Inspired by the competition exclusion principle, this work aims at providing a computational framework to explore the theoretical feasibility of viral co-infection as a possible strategy to reduce the spread of a fatal strain in a population. We propose a stochastic-based model—called Co-Wish—to understand how competition between two viruses over a shared niche can affect the spread of each virus in infected tissue. To demonstrate the co-infection of two viruses, we first simulate the characteristics of two virus growth processes separately. Then, we examine their interactions until one can dominate the other. We use Co-Wish to explore how the model varies as the parameters of each virus growth process change when two viruses infect the host simultaneously. We will also investigate the effect of the delayed initiation of each infection. Moreover, Co-Wish not only examines the co-infection at the cell level but also includes the innate immune response during viral infection. The resu...

Research paper thumbnail of A Network-based Comparison between Molecular Apocrine Breast Cancer Tumor and Basal and Luminal Tumors by Joint Graphical Lasso

IEEE/ACM Transactions on Computational Biology and Bioinformatics

Research paper thumbnail of F-MAP: A Bayesian approach to infer the gene regulatory network using external hints

PLOS ONE

The Common topological features of related species gene regulatory networks suggest reconstructio... more The Common topological features of related species gene regulatory networks suggest reconstruction of the network of one species by using the further information from gene expressions profile of related species. We present an algorithm to reconstruct the gene regulatory network named; F-MAP, which applies the knowledge about gene interactions from related species. Our algorithm sets a Bayesian framework to estimate the precision matrix of one species microarray gene expressions dataset to infer the Gaussian Graphical model of the network. The conjugate Wishart prior is used and the information from related species is applied to estimate the hyperparameters of the prior distribution by using the factor analysis. Applying the proposed algorithm on six related species of drosophila shows that the precision of reconstructed networks is improved considerably compared to the precision of networks constructed by other Bayesian approaches.

Research paper thumbnail of Predicting Hepatitis B Monthly Incidence Rates Using Weighted Markov Chains and Time Series Methods

Hepatitis B (HB) is a major global mortality. Accurately predicting the trend of the disease can ... more Hepatitis B (HB) is a major global mortality. Accurately predicting the trend of the disease can provide an appropriate view to make health policy disease prevention. This paper aimed to apply three different to predict monthly incidence rates of HB. This historical cohort study was conducted on the HB incidence data of Hamadan Province, the west of Iran, from 2004 to 2012. Weighted Markov Chain (WMC) method based on Markov chain theory and two time series models including Holt Exponential Smoothing (HES) and SARIMA were applied on the data. The results of different applied methods were compared to correct percentages of predicted incidence rates. The monthly incidence rates were clustered into two clusters as state of Markov chain. The correct predicted percentage of the first and second clusters for WMC, HES and SARIMA methods was (100, 0), (84, 67) and (79, 47) respectively. The overall incidence rate of HBV is estimated to decrease over time. The comparison of results of the three models indicated that in respect to existing seasonality trend and non-stationarity, the HES had the most accurate prediction of the incidence rates.

Research paper thumbnail of wpLogicNet: logic gate and structure inference in gene regulatory networks

Bioinformatics

MotivationThe gene regulatory process resembles a logic system in which a target gene is regulate... more MotivationThe gene regulatory process resembles a logic system in which a target gene is regulated by a logic gate among its regulators. While various computational techniques are developed for a gene regulatory network (GRN) reconstruction, the study of logical relationships has received little attention. Here, we propose a novel tool called wpLogicNet that simultaneously infers both the directed GRN structures and logic gates among genes or transcription factors (TFs) that regulate their target genes, based on continuous steady-state gene expressions.ResultswpLogicNet proposes a framework to infer the logic gates among any number of regulators, with a low time-complexity. This distinguishes wpLogicNet from the existing logic-based models that are limited to inferring the gate between two genes or TFs. Our method applies a Bayesian mixture model to estimate the likelihood of the target gene profile and to infer the logic gate a posteriori. Furthermore, in structure-aware mode, wpLo...

Research paper thumbnail of Evaluation of Toxoplasma gondii infection in western Iran: seroepidemiology and risk factors analysis

Tropical Medicine and Health, 2020

Background Toxoplasmosis is a parasitic infectious disease, and Toxoplasma gondii is the causativ... more Background Toxoplasmosis is a parasitic infectious disease, and Toxoplasma gondii is the causative factor of this intracellular protozoan disease. Due to the lack of information about the rate of T. gondii in general papulation of Markazi Province in Iran, the current study was conducted to determine the prevalence of toxoplasmosis and the related risk factor analysis in the general population of Markazi Province. Methods This cross-sectional study was performed within 6 months on individuals who were referred to diagnostic laboratories in Markazi Province. The demographic and background information of the subjects were collected using a questionnaire. Three milliliters of blood samples was collected from the participants under sterile conditions. The sera were separated and evaluated for levels of anti-Toxoplasma IgG antibody using a commercial enzyme-linked immunosorbent assay (ELISA) method. The collected data were analyzed by the SPSS software using descriptive statistics and ch...

Research paper thumbnail of Hepatogenesis and hepatocarcinogenesis: Alignment of the main signaling pathways

Journal of Cellular Physiology

Research paper thumbnail of Competitive exclusion during co-infection as a strategy to prevent the spread of a virus: A computational perspective

PLOS ONE, 2021

Inspired by the competition exclusion principle, this work aims at providing a computational fram... more Inspired by the competition exclusion principle, this work aims at providing a computational framework to explore the theoretical feasibility of viral co-infection as a possible strategy to reduce the spread of a fatal strain in a population. We propose a stochastic-based model—called Co-Wish—to understand how competition between two viruses over a shared niche can affect the spread of each virus in infected tissue. To demonstrate the co-infection of two viruses, we first simulate the characteristics of two virus growth processes separately. Then, we examine their interactions until one can dominate the other. We use Co-Wish to explore how the model varies as the parameters of each virus growth process change when two viruses infect the host simultaneously. We will also investigate the effect of the delayed initiation of each infection. Moreover, Co-Wish not only examines the co-infection at the cell level but also includes the innate immune response during viral infection. The resu...

Research paper thumbnail of A Network-based Comparison between Molecular Apocrine Breast Cancer Tumor and Basal and Luminal Tumors by Joint Graphical Lasso

IEEE/ACM Transactions on Computational Biology and Bioinformatics

Research paper thumbnail of F-MAP: A Bayesian approach to infer the gene regulatory network using external hints

PLOS ONE

The Common topological features of related species gene regulatory networks suggest reconstructio... more The Common topological features of related species gene regulatory networks suggest reconstruction of the network of one species by using the further information from gene expressions profile of related species. We present an algorithm to reconstruct the gene regulatory network named; F-MAP, which applies the knowledge about gene interactions from related species. Our algorithm sets a Bayesian framework to estimate the precision matrix of one species microarray gene expressions dataset to infer the Gaussian Graphical model of the network. The conjugate Wishart prior is used and the information from related species is applied to estimate the hyperparameters of the prior distribution by using the factor analysis. Applying the proposed algorithm on six related species of drosophila shows that the precision of reconstructed networks is improved considerably compared to the precision of networks constructed by other Bayesian approaches.

Research paper thumbnail of Predicting Hepatitis B Monthly Incidence Rates Using Weighted Markov Chains and Time Series Methods

Hepatitis B (HB) is a major global mortality. Accurately predicting the trend of the disease can ... more Hepatitis B (HB) is a major global mortality. Accurately predicting the trend of the disease can provide an appropriate view to make health policy disease prevention. This paper aimed to apply three different to predict monthly incidence rates of HB. This historical cohort study was conducted on the HB incidence data of Hamadan Province, the west of Iran, from 2004 to 2012. Weighted Markov Chain (WMC) method based on Markov chain theory and two time series models including Holt Exponential Smoothing (HES) and SARIMA were applied on the data. The results of different applied methods were compared to correct percentages of predicted incidence rates. The monthly incidence rates were clustered into two clusters as state of Markov chain. The correct predicted percentage of the first and second clusters for WMC, HES and SARIMA methods was (100, 0), (84, 67) and (79, 47) respectively. The overall incidence rate of HBV is estimated to decrease over time. The comparison of results of the three models indicated that in respect to existing seasonality trend and non-stationarity, the HES had the most accurate prediction of the incidence rates.