Network Modeling Analysis in Health Informatics and Bioinformatics This is an RSS file. You can use it to subscribe to this data in your favourite RSS reader or to display this data on your own website or blog.

Network alignment and motif discovery in dynamic networks
We reported how several issues may be transferred from static to dynamic networks by taking into account the temporal information. Furthermore, we encountered a systematic convergence toward iterative strategies both for ne twork alignment and motif discovery, justified by the fact that a dynamic network is usually analyzed through the sub-analysis of its time points. (Source: Network Modeling Analysis in Health Informatics and Bioinformatics)
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - October 3, 2022 Category: Bioinformatics Source Type: research

Prediction of solubility of some dihydropyridine derivative drugs in supercritical fluid carbon dioxide by RBFNN
In this study, a radial basis function neural network (RBFNN) was used to predict the solubility of some 1,4-dihydropyridine derivative drugs in supercritical fluid carbon dioxide. The solubility of drugs was predicted based on the pressure, temperature, molecular weight, melting point, density, carbon number, and hydrogen number. The predicted solubility obtained by RBFNN was compared to experimental data. The root mean square error (RMSE), determination coefficient (R2), mean bias error, mean absolute error, modified agreement index (md), and modified Nash and Sutcliffe efficiency were determined. The square regression c...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - September 30, 2022 Category: Bioinformatics Source Type: research

Prediction of enhanced bipolar disorder in autistic children using denoising convolutional neural network
AbstractBipolar disorder (BD) causes depression, anxiety, irritability, hyperactivity, and other behavioral changes in autistic children. An accurate BD examination helps the doctors to prescribe the correct treatment and dosage level. Patients with BD have previously undergone the Aberrant Behavior Checklist (ABC) in clinics for examination and which takes only a short amount of time. Continuous monitoring of autistic children is a major problem for physicians when assessing autistic children ’s examinations. In this paper, autistic child BD assessment is performed through the thermal radiometric pixel of facial regions...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - September 29, 2022 Category: Bioinformatics Source Type: research

Trends and challenges of image analysis in facial emotion recognition: a review
This study offers a thorough overview of FER processes as well as a comparison of some of the efficient methods. Furthermore, this survey will aid scholars in better understanding many types of challenges in the field of emotion detection. The PRISMA model representation is also addressed in this study. (Source: Network Modeling Analysis in Health Informatics and Bioinformatics)
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - September 23, 2022 Category: Bioinformatics Source Type: research

Integrated in silico functional analysis predicts autism spectrum disorders to be burdened by deleterious variations within CHD8 core domains and its CHD7-binding motif
AbstractAutism spectrum disorder (ASD) is a neurodevelopmental disorder presenting with social and communication deficits, restricted, repetitive behaviours and interest. Several recurrently mutated genetic risk factors have been implicated in ASD manifestation.Chromodomain helicase remodeller(CHD8) is one such master regulator mediating the expression of genes controlling neuron functions. We collected 8124 exonic SNPs inCHD8 from four databases representing the general and ASD populations and subjected them to multi-layered analyses on  >  25 computational tools. We observed that nsSNPs were common in the general ...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - September 21, 2022 Category: Bioinformatics Source Type: research

5-HTR2B and SLC6A3 as potential molecular targets of sertraline in the treatment of major depressive disorder: the use of bioinformatics and its practical implication
AbstractMajor depressive disorder (MDD) is known to be a highly limiting and disabling disorder worldwide. The main management for this disorder is based on pharmacological therapy with antidepressants, especially in moderate to severe presentations. Among these, selective serotonin reuptake inhibitors (SSRIs) are, at the moment, the most widely prescribed class. Individualized pharmacological therapy presents itself as a powerful tool to reduce the course of the disorder, especially if one takes into account the potential molecular targets and the relationship of these targets in MDD pharmacotherapy. To explore this possi...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - September 21, 2022 Category: Bioinformatics Source Type: research

SARS-CoV-2 transmission in university classes
AbstractWe investigate transmission dynamics for SARS-CoV-2 on a real network of classes at Simon Fraser University. Outbreaks are simulated over the course of one semester across numerous parameter settings, including moving classes above certain size thresholds online. Regression trees are used to analyze the effect of disease parameters on simulation outputs. We find that an aggressive class size thresholding strategy is required to mitigate the risk of a large outbreak, and that transmission by symptomatic individuals is a key driver of outbreak size. These findings provide guidance for designing control strategies at ...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - August 27, 2022 Category: Bioinformatics Source Type: research

Identification of small molecules against the NMDAR: an insight from virtual screening, density functional theory, free energy landscape and molecular dynamics simulation-based findings
AbstractAlzheimer ’s disease (AD) is a chronic intensifying neurodegenerative disorder and accounts for three fourths of dementia cases. To date, there is no effective treatment available which can completely cure AD. The available medications can slower AD progression and can provide symptomatic relaxation. The N- methyl-d-aspartate receptor (NMDAR) plays a paramount role in the survival of neurons and synaptic plasticity. It is also involved in several other diseases. Although, excessive function of NMDAR cause excitotoxicity. Due to this the cell death process activated resulting into neurodegeneration and promotes AD...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - August 23, 2022 Category: Bioinformatics Source Type: research

Network pharmacology study to reveal underlying mechanisms, targets, and bioactives of Aralia cordata against obesity
AbstractAralia cordata (AC) has been used as anti-obesity herbal plants by Chinese, Japanese, and Korean, but its active chemical constituents, mechanism(s), and targets have not been documented completely. We aimed to investigate significant phytochemicals, pathways, and targets of AC against obesity via network pharmacology. The phytochemicals from AC were identified by Gas Chromatography –Mass Spectrometry (GC–MS) and were screened subsequently by Lipinski’s rule. The compound–target relationships were retrieved by analyzing SwissTargetPrediction, SEA search server. Then, obesity-related targets were identified ...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - August 9, 2022 Category: Bioinformatics Source Type: research

A complexity reduction based retinex model for low luminance retinal fundus image enhancement
AbstractRetinal fundus images play significant roles in the early detection and treatment of various ocular diseases. However, they are often suffered from low luminance in the process of shooting. To address this problem, we propose a Complexity Reduction Retinex (CR\(^2\)) model for the enhancement of low luminance retinal fundus images. The proposed method enables the divided illumination component to be spatially smooth and the reflectance component to be piece-wise continuous. Meanwhile, to improve the computational efficiency, we divide the illumination and reflection components into two independent sub-problems and ...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - August 9, 2022 Category: Bioinformatics Source Type: research

Identification of blood-based inflammatory biomarkers for the early-stage detection of acute myocardial infarction
This study aimed to identify the key genes for early AMI detection from the expression data of peripheral blood samples. We retrieved three GEO datasets from NCBI that represent expression data of healthy individuals and early-stage AMI patients. The differentially expressed genes (DEG) were determined from three datasets by the GEO2R tool on the NCBI webpage. The significant DEGs common in at least 2 datasets were identified by VENNY 2.1 web tool. We then performed a functional enrichment analysis of the selected genes and also the potential hub genes possibly involved in AMI were predicted by a protein –protein interac...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - August 3, 2022 Category: Bioinformatics Source Type: research

Mathematical computation of the tumor growth
AbstractThe tumor is a vital concern in the medical system, and it is one of the causes of losing life and puts a big load on medical. Describing the tumor staging by analysis is a crucial subject for medical procedures. Advanced exposure to hidden metastasis indistinguishable from modern techniques would significantly impact the most appropriate concern and long-term survival. Researchers have been working to explain a new medical practice model for tumors. The tumor cells' population growth is dubious due to their strange response.  Metastasis dispersal is how some cells from the tumors move and shape different tumors....
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - July 27, 2022 Category: Bioinformatics Source Type: research

Novel mathematical model based on cellular automata for study of Alzheimer ’s disease progress
AbstractIn recent years, extensive research has been done on the prediction, treatment, and recognition of Alzheimer ’s disease (AD). The study of AD emerging and progression in the first years is valuable due to the nature of AD. Among scientific works, mathematical modeling of AD is an efficient way of studying the influence of various parameters on AD emerging. This paper proposes a novel model based on Cellu lar Automata (CA) for the study of AD's progress. In our model, the synapses of each neuron have been considered as square cells located around the central cell. The key parameter for AD progression in our model ...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - July 23, 2022 Category: Bioinformatics Source Type: research

Diagnosing COVID-19 using artificial intelligence: a comprehensive review
AbstractIn early March 2020, the World Health Organization (WHO) proclaimed the novel COVID-19 as a global pandemic. The coronavirus went on to be a life-threatening infection and is still wreaking havoc all around the globe. Though vaccines have been rolled out, a section of the population (the elderly and people with comorbidities) still succumb to this deadly illness. Hence, it is imperative to diagnose this infection early to prevent a potential severe prognosis. This contagious disease is usually diagnosed using a conventional technique called the Reverse Transcription Polymerase Chain Reaction (RT-PCR). However, this...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - July 12, 2022 Category: Bioinformatics Source Type: research

SGAClust: Semi-supervised Graph Attraction Clustering of gene expression data
AbstractGene expression data clustering groups genes with similar patterns into a group, while genes exhibit dissimilar patterns into different groups. Traditional partitional gene expression data clustering partitions the entire set of genes into a finite set of clusters which might not reflect co-expression or coherent patterns across all genes belonging to a cluster. In this paper, we propose a graph-theoretic clustering algorithm called GAClust which groups co-expressed genes into the same cluster while also detecting noise genes. Clustering of genes is based on the presumption that co-expressed genes are more likely t...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - June 21, 2022 Category: Bioinformatics Source Type: research