Disease discovery-based emotion lexicon: a heuristic approach to characterise sicknesses in microblogs
This study proposes a heuristic mechanism by using an unsupervised learning technique to efficiently detect disease incidents and outbreaks from the tweet content. We categorised the types of emotions that are highly linked to a specific disease and its related terminologies. Emotions (anger, fear, sadness, and joy) and diabetes-related terminologies were extracted using the NRC Affect Intensity Lexicon and part-of-speech tagging tool. A two-cluster solution was established and validated. The classification results showed that K-means clustering with two centroids had the highest classification accuracy (96.53%). The relat...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - September 22, 2020 Category: Bioinformatics Source Type: research

Improving the performance of P300 BCI system using different methods
AbstractA brain –computer interface (BCI) can be used for people with severe physical disabilities such as ALS, or amyotrophic lateral sclerosis. BCI can allow these individuals to communicate again by creating a new communication channel directly from the brain to an output device. BCI technology can allow paral yzed people to share their intent with others, and thereby demonstrate that direct communication from the brain to the external world is possible, and that it might serve useful functions. In this paper, we propose a system to exploit the P300 signal in the brain, a positive deflection in event-rela ted pote...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - September 21, 2020 Category: Bioinformatics Source Type: research

Moment invariants for cancer classification based on electron –ion interaction pseudo potentials (EIIP)
AbstractCancer is considered one of the most dangerous diseases leading to imminent death during recent decades. It spreads quickly at a frightening pace to all parts of the body and early detection of such diseases may help reduce the risks. Many methods have been used to classify and predict the outcome of cancer, such as image processing techniques, artificial intelligence, and nanotechnology. Out of these methods, artificial intelligence techniques have played an essential role and have provided satisfying results from different investigations in various fields. Considering that cancer is a genetic disease, electron &n...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - September 20, 2020 Category: Bioinformatics Source Type: research

Improved identification of core biomarkers and drug repositioning for ovarian cancer: an integrated bioinformatics approach
In this study, we introduced a rule for modification of outlier to improve the performance of biomarker selection methods. We employed the proposed procedure on simulated and three publicly available ovarian cancer gene expression datasets, and improved performance of the proposed procedure was observed. We identified 226 differentially expressed genes (DEGs) overlapped i n 3 proposed modified microarray OC datasets using LIMMA in R. These DEGs were underwent Gene Ontology analysis and revealed apoptotic signaling and programmed cell death as an important biological process. The pathway enrichment analysis showed molecular...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - September 11, 2020 Category: Bioinformatics Source Type: research

Reconstruction of 5D cardiac MRI through the blood flow registration: simulation of the fifth dimension and assessment of the left ventricular ejection fraction
This study included 18 patients who underwent 1.5  T cardiac MRI for different etiologies: a total of 395 series and 18,483 scans was tested. The estimated values with the classical method of segmentation by contour with extreme (LVFE) in the sample was compared. A registration algorithm was implemented, with mean elapsed time registration = 0 .5 s. The range of (LVFE) varied between [20 and 87%] shows that the results are satisfactory for the experts by comparing with the clinical assessment for the study of the anomalies of myocardial contractility and kinetic abnormalities and the error rate was ...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - September 9, 2020 Category: Bioinformatics Source Type: research

In silico evaluation of inhibitory potential of novel triazole derivatives against therapeutic target myristoyl-CoA: protein N -myristoyltransferase (NMT) of Candida albicans
AbstractThis paper explores the confluence of genetic algorithm-multiple linear regression (GA-MLR) based quantitative structure –activity relationship (QSAR) modeling and molecular docking simulation studies relevant to the novel and effective triazole derivatives as NMT inhibitors in an attempt to develop superior antifungal activity coupled with less susceptibility to develop resistance. Initially, thirteen penta-variant models were generated through hybrid GA-MLR based QSAR approach. Eventually, a general pooled model was derived through the collective consideration of all the descriptors incorporated in the stat...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - August 20, 2020 Category: Bioinformatics Source Type: research

RxBlock: Towards the design of a distributed immutable electronic prescription system
AbstractBlockchains have received much hype lately and researchers and developers are seeking unique and innovative uses for this new technology. The medical field is no exception, specifically pharmaceutical uses for blockchains. To this effect, this proposed research aims to design a secure and efficient electronic prescription system leveraging blockchain technology. Using the unique properties of blockchains, the proposed application (RxBlock) seeks to explore how a blockchain could be used in electronic prescriptions. The proposed application createsan immutable ledger of transactions  occurring over a network. T...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - August 10, 2020 Category: Bioinformatics Source Type: research

QSAR modeling of anti-HIV activity for DAPY-like derivatives using the mixture of ligand-receptor binding information and functional group features as a new class of descriptors
AbstractAn accurate QSAR model was developed for the prediction of the anti-HIV activities of a set of DAPY-like derivatives as new non-nucleoside reverse transcriptase inhibitors (NNRTIs). The ligand –receptor (LR) interactions for all compounds were studied by the docking of compounds in the active site of appropriate receptors. The binding information of LR complexes at the best pose was called the molecular docking descriptors (MDDs). The mixture of 10 MDDs with about 154 simple, functional group counts was used as a new group of descriptors in the QSAR study of DAPY-like compounds. Among the 164 mixed descriptor...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - August 10, 2020 Category: Bioinformatics Source Type: research

A COVID-19 infection risk model for frontline health care workers
In this study, we formulate a theoretical model to calculate the risk of being infected in health care facilities considering the following factors: the average number of encounters with a suspected COVID-19 patient per hour; interaction time for each encounter; work shift duration or exposure time; crowd density, which may depend on the amount of space available in a given location; and availability and effectiveness of protective gears and facilities provided for the frontline health care workers. Based on the simulation results, a set of risk assessment criteria is proposed to classify risks as ‘low’, &lsquo...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - August 8, 2020 Category: Bioinformatics Source Type: research

Molecular docking suggests repurposing of brincidofovir as a potential drug targeting SARS-CoV-2 ACE2 receptor and main protease
AbstractThe current outbreak of the highly transmittable and life-threatening severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has evolved rapidly and posed a global health emergency. Many clinical trials are now being conducted to test possible therapies. To assist this, virtual screening via molecular docking was performed on several FDA-approved drugs, previously used in epidemics, and the top ten compounds were selected. These ten well-characterized drugs, previously used to treat malaria and Ebola infections, were screened based on their interactions with the SARS-CoV-2 ACE2 receptor and 3C-like protease. ...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - August 8, 2020 Category: Bioinformatics Source Type: research

Network-based disease gene prioritization based on Protein –Protein Interaction Networks
AbstractThe process to identify genes responsible for a disease is a complex task. The various experimental techniques developed to identify disease-causing genes suffer from the problem of high-cost and high time consumption. Thus, with the increasing amount of biological information available online various computational techniques have been developed to complete this complex task of identification of disease-causing genes. A more accepted view is that the genes related to similar diseases reside in the same neighborhood of the molecular network. In this review, various categories of computational techniques for disease ...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - August 6, 2020 Category: Bioinformatics Source Type: research

In silico molecular studies of natural compounds as possible anti-Alzheimer ’s agents: ligand-based design
This study focused on virtual screening of ~ 33,000 natural compounds to find potential BACE1 inhibitors. Multiple ligands pharmacophore model was generated using PHASE to screen retrieved compounds against a four-site (ADDR) hypothesis. Molecular docking was performed to predict the binding status of the natural compounds. Based on binding affinity, the top eight compounds were chosen for further analysis. The docked complexes were analyzed for binding free energy using PRIME MM/GBA calculation. The compounds were filtered for drug-likeness using ADME/TOX (absorption, distribution, metabolism, excretion and toxicit...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - August 4, 2020 Category: Bioinformatics Source Type: research

LM-ANN-based QSAR model for the prediction of pEC 50 for a set of potent NNRTI using the mixture of ligand –receptor interaction information and drug-like indexes
AbstractA combination of ligand –receptor interactions and drug-like indexes have been used to develop a quantitative structure–activity relationship model to predict anti-HIV activity (pEC50) of 73 azine derivatives as non-nucleoside reverse transcriptase inhibitors. Ligand –receptor interactions were derived from the best position (best pose) of studied compounds, as ligands, in the active site of receptors using Autodock 4.2 software and named as molecular docking descriptors. The drug-like indexes were calculated using DRAGON 5.5 software. Two groups of descriptor s were mixed, and the stepwise regres...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - July 24, 2020 Category: Bioinformatics Source Type: research

Correction to: A multi ‑target approach for discovery of antiviral compounds against dengue virus from green tea
In results and discussion section, the description of figures was revised as follows. In the case of NS1-Compound-1 complex, consider an additional contact of Glu12 (Fig.  1a), in case of NS1-Compound-2 complex, six instead of four residues were involved in contact (Fig. 1b). In case of RDRP-Compound-1 complex, seven instead of three hydrogen bonds were formed (Fig. 1d), while in case of RDRP Compound-2 complex nine instead of seven hydrogen bonds were recorded (F ig. 1e). In case of MTD-complex 1 consider an addition contact of Leu17 (Fig. 1g). (Source: Network Modeling Analysis in Health Informat...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - July 23, 2020 Category: Bioinformatics Source Type: research

Self ‐care management importance in kidney illness: a comprehensive and systematic literature review
AbstractKidney illness is a key problem for individuals ’ health across the world and a significant reason for death, too. Therefore, education and management are essential for prevention and treatment. Promoting self-management through improving patient self-efficacy may have lasting advantages as the management of kidney disease will bring positive r esults for the patient. However, the count of patients having incorrect self‐care conducts is still growing even with constant health education. Knowledge and self‐efficacy are the main parameters affecting self‐care conduct. Nevertheless, there are very few work...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - July 17, 2020 Category: Bioinformatics Source Type: research

Identification of vital regulatory genes with network pathways among Huntington ’s, Parkinson’s, and Alzheimer’s diseases
AbstractIn the world, Huntington ’s disease, Parkinson’s disease, and Alzheimer’s disease are reported as the most deadly diseases to issue common disorders for human beings. In state-of-the-art works, it is well studied that Huntington’s disease (HD) and Parkinson’s disease (PD) are affected by genetic factors and common motor system disorder, respectively. On the other hand, Alzheimer’s disease (AD) is a neurodegenerative disorder which is categorized by age-related dementia, behavioral changes, and memory loss, etc. In the literature, it is also identified that lots of similar genetic...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - July 16, 2020 Category: Bioinformatics Source Type: research

Structure-based virtual screening, molecular docking and dynamics studies of natural product and classical inhibitors against human dihydrofolate reductase
AbstractFolate antagonists are classified as important and valuable therapeutic agents against infection, neoplastic, and inflammatory diseases. Dihydrofolate reductase (DHFR) is a biological target of two well-defined folate antagonists, classical and non-classical inhibitors. DHFR catalyzes the reduction of 7,8-dihydrofolate to 5,6,7,8-tetrahydrofolate benefits of NADPH as a cofactor. With the point to recognize new chemicals to be utilized for further structure-based drug design, a collection of 67753 molecules including chemicals and natural products have been screened through the docking method from the Zinc Database....
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - July 12, 2020 Category: Bioinformatics Source Type: research

Multiple sclerosis: an associated single-nucleotide polymorphism study on Egyptian population
This study was applied over an Egyptian dataset of 38 MS patients and 35 controls. Hence, different models were applied, Dom inant, Recessive and Genotypic models along with Fisher’s Exact method, Basic case–control analysis and Logistic regression analysis. This paper shows that the SNPs rs1625579, rs57095329, rs767649 and rs3027898 are associated with MS (p value  
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - July 8, 2020 Category: Bioinformatics Source Type: research

Detecting disease-related SNP loci based on GSP
AbstractA large number of studies have shown that susceptibility to some diseases may be related to some SNP (Single Nucleotide Polymorphism) loci. Accurate location of disease-related SNP loci can help people understand the pathogenesis of diseases and prevent them from happening. Based on Graph Signal Processing (GSP) theory, this paper proposes a novel method called GSP to detect disease-related SNP loci. GSP method is divided into five steps. The first step is to establish a graph signal model of all SNP loci. The second step is to extract the high-frequency components of graph signal with a high-pass filter. The third...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - July 2, 2020 Category: Bioinformatics Source Type: research

Molecular docking study of the anticandida activity some schiff bases and their complexes
AbstractThe research study entails the molecular docking study of some recently designed Schiff base complexes and their ligands (Schiff base) on two receptors, a crystal structure ofCandida albicans Mep2 (5AF1) and a thiamin pyrophosphokinase fromCandida albicans (2G9Z). These two receptors were used to investigate the inhibitory potentials of some Schiff bases on candida albicans when coupled with a central metal atom. The docking results for 2G9Z the complex A3 had the best binding affinity of 21.473  kcal/mol, while for 5AF1 the complex A4 best inhibits the crystal structure with a binding affinity of 23.518 ...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - June 30, 2020 Category: Bioinformatics Source Type: research

A principal component regression model for predicting phytochemical binding to the H. pylori CagA protein
In this study, a predictive model for the binding free energy of natural compounds towards the cagA protein is presented. The formulated model which is built on principal component —multiple linear regression demonstrates reliable accuracy (r2test = 0.92, RMSEtest = 0.483), while only requiring five independent variables for the prediction. It was further noted that topological descriptors had the greatest influence on the generated principal components which served as the predictors. The created regression model can help promote and accelerate the disco very of natural compounds as cagA b...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - June 25, 2020 Category: Bioinformatics Source Type: research

Correction to: Process mining project methodology in healthcare: a case study in a tertiary hospital
The acknowledgment section has been published missing some names in the online published article. (Source: Network Modeling Analysis in Health Informatics and Bioinformatics)
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - June 22, 2020 Category: Bioinformatics Source Type: research

A novel approach to identify subtype-specific network biomarkers of breast cancer survivability
ConclusionThis method can be used to identify the survivability of breast cancer patients using gene relationship networks. It has high prediction performance, including specificity and sensitivity for both cohorts of survivals and deceased. (Source: Network Modeling Analysis in Health Informatics and Bioinformatics)
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - June 20, 2020 Category: Bioinformatics Source Type: research

Enhancing convolution-based sentiment extractor via dubbed N-gram embedding-related drug vocabulary
AbstractEveryday patients ’ narratives on social media can reveal crucial public health issues. Mining those online narratives, which remained so far unconsidered, may mirror further hidden patient health status. Deep learning-based sentiment analysis (SA) approaches broadly focus on grammar directions such as semantic dir ection or only center on extract sentiment words. They provide both richer representation capabilities and better performance but do not consider the related medication concepts. As a result, the inaccurate recognition of related drug entities may seriously fail to retrieve the relevant sentiment e...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - June 17, 2020 Category: Bioinformatics Source Type: research

A regression-based model for predicting the best mode of treatment for Egyptian liver cancer patients
In this study, we analyzed the data of 1427 Egyptian patients with liver cancer who were either treated by one of five different treatment methods or not treated. We proposed and compared between two pipelines, a Single-Model pipeline and a Multi-Model pipeline, for analyzing th e patient’s clinical and genetic data to recommend the best liver cancer treatment and, therefore, potentially improve their prognosis. We studied the performance of six regression methods in predicting the outcome of the treatment modalities for liver cancer patients. The best performing method w as used in building the models in the propose...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - June 11, 2020 Category: Bioinformatics Source Type: research

Evaluation of the prognostic significance of CDK6 in breast cancer
AbstractCyclin-dependent kinase (CDK) gene family is an important cell cycle progression regulator, which may function as a tumor suppressor. We performed a systematic onco-informatics analysis to investigate the prognostic value ofCDK6 in breast cancer.CDK6 expression was evaluated using the Oncomine and UALCAN database. The relevance betweenCDK6 level and clinical parameters and survival data in breast cancer was analyzed using the bc-GenExMiner, and Kaplan –meier plotter databases. The methylation status and heat map ofCDK6 were analyzed by utilizing the UCSC Xena and UALCAN. It was identified thatCDK6 was under-e...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - June 11, 2020 Category: Bioinformatics Source Type: research

In silico vaccine design against Chlamydia trachomatis infection
This study identifies the putative vaccine candidates that are membrane bound with high antigenicity properties; antigenicity induces the immunogenicity which involves identification of T-cell and B-cell epitopes that induce both humoral and cell-mediated immunity. The epitopes ‘LSWEMELAY’, ‘LSNTEGYRY’, ‘TSDLGQMEY’, ‘FIDLLQAIY’ and ‘FSNNFSDIY’ were predicted as core sequences for class I MHC molecules. The identified epitopes showed promising ability to interact with the human leukocyte antigens (HLA). These epitopes showed maximum population coverage w ith epitop...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - June 10, 2020 Category: Bioinformatics Source Type: research

Identification of Multiple Sclerosis lesion subtypes and their quantitative assessments with EDSS using neuroimaging
This article presents a technique to classify MS lesion subtypes in MR images and then evaluates the correlation between lesion subtypes and Expanded Disability Status Scale (EDSS). The technique used textural features based on the Gray Level Co-occurrence Matrix (GLCM) and histogram information (mean and variance) to describe each lesion and normal tissue of FLAIR Images. Then it discriminated them with Support Vector Machine (SVM). A comprehensive post-processing module improved the quality of segmentation. We found corresponding areas in T2-weighted (T2-w), T1-weighted (T1-w) called black holes, and T1-weighted enhancin...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - June 8, 2020 Category: Bioinformatics Source Type: research

Machine learning approach for wart treatment selection: prominence on performance assessment
AbstractWarts are benign tumors, caused by human papillomavirus (HPV). The present study mainly emphasis on the selection of suitable methods for the removal of a common and plantar wart. There are numerous wart treatment methods for this disease, among them cryotherapy and immunotherapy are well-known approaches. Identifying the suitable wart treatment method manually is quite challenging. Moreover, existing machine learning (ML) techniques show a poor prediction accuracy towards the selection of wart treatment method, however, the prediction accuracy is not satisfactory and can be further improved. To achieve the same, t...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - June 3, 2020 Category: Bioinformatics Source Type: research

Using Twitter for diabetes community analysis
AbstractSocial media platforms have become a common venue for sharing experiences and knowledge about health-related topics. This research focuses on examining social media-based communication patterns related to diabetes on the Twitter platform. Specifically, we apply an updated methodology to examine changes in the current use of hash-tags, trending hash-tags, and the frequency of diabetes-related tweets using a previous study as a baseline. Our results show significant growth in the diabetes community on Twitter over time and also evidence that this community is increasing in its capacity to spread awareness regarding d...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - June 2, 2020 Category: Bioinformatics Source Type: research

Impact of deep sequencing on hepatocellular carcinoma utilizing high-throughput technology
In this study, next-generation sequence (NGS) is utilized by applying OncoSNP-SEQ technique to a number of human chromosomes for analyzing hepatic cancer data that identify genome-wide mutations in copy number of the genomic information data. The outcomes referred to a certain number of chromosome aberrations detected with significant genes such as: SHC, TCP1, CCT3,SHC1, EPHA5, UGT2B28, UBE1L2, and also strike (CREB3L4, RAB1, MAGI2) genes which are discovered lately in 2013, tumor suppressorsSHC1 andCKS1B, LRP1B, as well as oncogeneUBE1L2, all of which may play a central role in cancer cell survival during the progress of ...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - May 26, 2020 Category: Bioinformatics Source Type: research

Breast cancer classification with reduced feature set using association rules and support vector machine
AbstractIn the last few years, machine learning is one of the driving forces of science and industry, but increasing of data requires paradigm shifts in traditional methods in the application of machine learning techniques on this data especially in healthcare field. Furthermore, with the availability of different clinical technologies, tumor features have been collected for breast cancer classification. Therefore, feature selection and accuracy improvement have become a challenging and time-consuming task. In this paper, the proposed approach has two stages. In the first, Association Rules (AR) are used to eliminate insig...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - May 21, 2020 Category: Bioinformatics Source Type: research

A real-time biosurveillance mechanism for early-stage disease detection from microblogs: a case study of interconnection between emotional and climatic factors related to migraine disease
This study paves the way to discover disease-related features using both emotional and climatic factors. (Source: Network Modeling Analysis in Health Informatics and Bioinformatics)
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - May 14, 2020 Category: Bioinformatics Source Type: research

Comparative analysis of ROS-scavenging gene families in finger millet, rice, sorghum, and foxtail millet revealed potential targets for antioxidant activity and drought tolerance improvement
In this study, we compared structural and functional aspects of antioxidant genes  viz., APX, DHAR, MDHAR, GR, and SOD of two contrasting genotypes  viz. GP-1 (low Ca2+) and GP-45 (high Ca2+) of finger millet with other cereal crops such as rice, sorghum, and foxtail millet. The structural analysis shows that all genes are conserved and shares almost the same domains such as ascorbate peroxidase, glutathione dehydrogenase, glutathione reductase, Fe, and Cu –Zn superoxide dismutase domains which play a significant role in antioxidant activity and drought tolerance. These genes were mainly localized in c...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - May 14, 2020 Category: Bioinformatics Source Type: research

Effect of hospital architecture, computer games, and nurses ’ behavior on the effectiveness of the treatment process of adolescent cancer patients
AbstractCancer patients suffer from many physical, psychological, and social problems that may impede quality of life and reduce the impact of treatment. Researchers have concluded that in addition to focusing on the treatment of the disease in the form of drugs and chemotherapy, factors such as the physical environment, communication skills of physicians and nurses with patients, increased hope, quality of life, knowledge of the disease, causing the immune system of patients with cancer is be strengthened. The influential role of therapeutic places can be effective in the outcome and treatment of adolescents and children ...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - May 6, 2020 Category: Bioinformatics Source Type: research

De novo modeling and structural characterization of IL9-IL9 receptor complex: a potential drug target for hematopoietic stem cell therapy
AbstractHematopoietic stem cell therapy can control disease-related complications in neonatal disorders of newborns. The IL9-IL9R complex is one of the most multifunctional cytokine complexes that promote proliferation and differentiation of hematopoietic progenitors. However, the structure of this complex has not been determined yet. The present work demonstrates a de novo computational method for rational protein designing to recapitulate the structural relationship among IL9: IL9R complex. We employed a strategy to design mimics of IL-9 that binds to IL-9R α by molecular modeling and protein–protein docking ...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - April 22, 2020 Category: Bioinformatics Source Type: research

In silico molecular docking analysis of cancer biomarkers with GC/MS identified compounds of Scytonema sp.
This study was aimed to perform pre-clinical evaluation of the gas chromatography –mass spectrometry (GC/MS) identified bioactive compounds of cyanobacteriumScytonema sp. MGL002 as an anticancer drug resource using in silico docking approaches. Among the twenty GC/MS identified cyanobacterial compounds, only four of them viz. tetradecanoic acid; palmitoleic acid; 9,12-octadeca dien-1-ol, (Z,Z)- and 6-octadecanoic acid (Z)- were found to be potent anticancer therapeutic agent through molecular docking study. These anticancerous compounds were also accepted as a potent drug-like compound through Lipinski drug likelines...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - April 22, 2020 Category: Bioinformatics Source Type: research

Process mining project methodology in healthcare: a case study in a tertiary hospital
AbstractProcess mapping in the healthcare environment provides several managerial benefits, which are reflected in the quality of patient care. Among the ways to map the processes, a method called"process mining" has been used in several contexts and has presented interesting results. However, there is a lack of studies focused on the standardisation of the process mining application process. To bridge this gap, the present study developed a methodology for the application of process mining in healthcare entitled Process Mining Project Methodology in Healthcare (PM2HC). This methodology was developed over a serie...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - April 15, 2020 Category: Bioinformatics Source Type: research

Feature selection and pattern recognition for different types of skin disease in human body using the rough set method
AbstractDisease analysis is one of the applications of data mining. The rough set is knowledge and information based method to help human decision-making, learning, and activity. Many researchers have put forward their findings in the study of skin diseases, but the feature selection and the pattern recognition of different types of skin disease by taking a standard set of the large platform (taking as parameters) have not been seen yet using the rough set method. We use histopathological skin data samples to exhibits strategy for multi-source, multi-methodology, and multi-scale data frameworks. This realistic evaluation s...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - April 13, 2020 Category: Bioinformatics Source Type: research

A tri-nucleotide mapping scheme based on residual volume of amino acids for short length exon prediction using sliding window DFT method
AbstractOne of the great challenges in the field of bioinformatics is how to locate the accurate protein-coding regions in a given DNA sequence. The accurate identification of the protein-coding region is useful in many applications. For instance; it helps in characterizing new proteins, drug designing, and also in revealing the evolutionary background of a particular organism. DSP based techniques are quite popular in the protein-coding region identification. The first essential step of the DSP based exon prediction technique is to convert the base sequences into the numerical sequence. The choice of the numerical mapping...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - April 8, 2020 Category: Bioinformatics Source Type: research

Mathematical analysis based on eigenvalue approach to study liver metastasis disease with applied drug therapy
AbstractThe basic reaction –diffusion model is extended to study liver metastasis disease with applied drug therapy by the term which describes the interaction between the tumor and normal cells. The drug therapy is taken as a function of tumor shape as well as time duration. The model is solved using an analytical eigenval ue approach. The results obtained from the model are presented graphically for different case studies to show the response of tumor decay and growth respectively in the presence and absence of the drug therapy. Finally, the model outcome and their simulations are compared with the known clinical r...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - April 7, 2020 Category: Bioinformatics Source Type: research

Clinicopathological and prognostic significance of GPC3 in human breast cancer and its 3D structure prediction
AbstractGlypican-3 (GPC3) is a heparan sulfate proteoglycan that may function as a tumor suppressor in breast cancer (BC). To evaluate the prognostic value of GPC3 in BC, systematic analysis was performed in this study. To evaluate gene alteration during breast carcinogenesis, GPC3 expression was analyzed using the Oncomine, GENT, UALCAN, bcGenExMiner, and UCSC Xena databases. The prognostic role of GPC3 in BC was investigated using KM Plotter and PrognoScan databases. Promoter methylation status and heat map of GPC3 were determined using UALCAN and UCSC Xena. GPC3 expression was significantly downregulated in BC compared ...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - April 5, 2020 Category: Bioinformatics Source Type: research

A comparison and analysis of the Twitter discourse related to weight loss and fitness
This study aims at understanding tweets stated on the amount of reception shown by people in the course of weight loss in a period of 1  month. This study uses cross-sectional and descriptive method to analyze over 2,684,858 of tweets quantitatively. It also compares the emotional aspects present in the tweets. Users, who are active in this domain, are classified into six classes. An investigation and comparison of the number of ac tivities with relation to weight loss has been carried out by searching users’ geographical information of social networks in different continents. English tweets have been chosen bec...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - April 1, 2020 Category: Bioinformatics Source Type: research

Multi-modal social and psycho-linguistic embedding via recurrent neural networks to identify depressed users in online forums
AbstractDepression is the most common mental illness in the US, with 6.7% of all adults experiencing a major depressive episode. Unfortunately, depression extends to teens and young users as well and researchers have observed an increasing rate in recent years (from 8.7% in 2005 to 11.3% in 2014 in adolescents and from 8.8 to 9.6% in young adults), especially among girls and women. People themselves are a barrier to fighting this disease as they tend to hide their symptoms and do not receive treatments. However, protected by anonymity, they share their sentiments on the Web, looking for help. In this paper, we address the ...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - March 31, 2020 Category: Bioinformatics Source Type: research

Molecular docking and ADMET-based mining of terpenoids against targets of type-II diabetes
AbstractDespite the availability of various medicines for the treatment of diabetes, plant-based drugs draw special attention due to their low cost and lesser side effects. The rhizomes of plantHedychium coronarium have been reported for its anti-diabetic activity previously. In the present study, docking and computational ADME parameters of a few terpenoid ligands isolated from the above-mentioned plant against two control molecules (Sitagliptin, Metformin) were compared. The retrieved docked images indicated the docking sites in the target protein. Out of the five compounds, Digoxigenin monodigitoxoside has shown the bes...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - March 30, 2020 Category: Bioinformatics Source Type: research

A multi-target approach for discovery of antiviral compounds against dengue virus from green tea
AbstractDengue virus (DENV) infection is one of the largest threats worldwide, and there is no any specific drug available in the market to combat its serious causes. In the present study, we attempted to screen the potential of green tea to inhibit DENV infection through known DENV multi-target, viz. nonstructural protein 1 (NS1), RNA dependent RNA polymerase domain (RDRP), and methyltransferase domain of non-structural protein 5 (MTD). A total of 25 bioactive compounds from the green tea were docked against the selected targets  that result into only three compounds with substantial binding affinity above −&nb...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - March 14, 2020 Category: Bioinformatics Source Type: research

Prognostic significance of the Cdk5 gene in breast cancer: an in silico study
AbstractCyclin-dependent kinase 5 (Cdk5) functions as a tumor promoter in various types of cancer. Cdk5 is overexpressed in breast cancer patients. The prognostic significance of the Cdk5 gene and its expression in breast cancer were analyzed using various bioinformatic tools. Cdk5 gene expression in different breast cancer subtypes was analyzed using the Oncomine, UALCAN, and bcGenExMiner v4.2 websites. The correlation between Cdk5 mRNA expression and promoter methylation was established using TCGA datasets from the UCSC Xena and UALCAN websites. The relationship between Cdk5 promoter methylation and different clinicopath...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - March 14, 2020 Category: Bioinformatics Source Type: research

Time domain analysis on myoelectric activity of masseter muscles in resting and chewing conditions
The objective of this work is to record and analyze the electrical activity of themasseter muscle of healthy subjects during resting and chewing conditions. In this work, the electrical activity of themasseter muscle was recorded form healthy volunteers of different age, using non invasive surface electrodes. The EMG signals are recorded from left as well as right sides in resting and chewing conditions. The characteristics of the EMG signals in resting and chewing conditions are analyzed using various statistical measures, Fast Fourier Transforms (FFT) and Hjorth parameters such as complexity, activity, and mobility. Resu...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - March 12, 2020 Category: Bioinformatics Source Type: research

Modeling a global regulatory network of Methanothermobacter thermautotrophicus strain ∆H
AbstractGenome-scale regulatory networks are a great concern in studying the crucial problems in bacterial genome biology.Methanothermobacter thermautotrophicusΔH (MTH) is a model organism of thermophilic methanogenic archaea contributing to a large environmental impact in global carbon cycling and strain used in the biofuel industry. Nonetheless, systematic transcriptional regulations have not been previously made for this organism. In the present study, a global regulatory network of this organism was reconstructed and its associated molecular function revealed at systems-level. The inferred genome-wide regulatory ...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - March 6, 2020 Category: Bioinformatics Source Type: research

A study on MANOVA as an effective feature reduction technique in classification of childhood medulloblastoma and its subtypes
In this study, we examine whether the features are statistically significant for analysis towards classifying childhood MB from normal samples and its various subtypes, using MANOVA. Further, this technique is used as a feature reduction technique, which proves that it can be effectively used as such. Infact, the simplicity of the technique makes it a better choice when considering a sizeably high number of features. (Source: Network Modeling Analysis in Health Informatics and Bioinformatics)
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - March 5, 2020 Category: Bioinformatics Source Type: research