Network Modeling Analysis in Health Informatics and Bioinformatics 
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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.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 netwo...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - March 5, 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 4, 2020 Category: Bioinformatics Source Type: research
Visual-X2: interactive visualization and analysis tool for protein crystallization
AbstractIn high-throughput systems, the crystallization experiments require the inspection and analysis of a large number of trial images. The visualization and analysis tools are needed to view and analyze the experimental results, and recommend novel crystalline conditions by analyzing prior results. It is essential to integrate all these components into a single system. Therefore, we developedVisual-X2, an interactive visualization software developed to aid the user for quick and efficient visualization and analysis of the results of the experiments.Visual-X2 has a number of useful features for visualization and analysi...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - February 5, 2020 Category: Bioinformatics Source Type: research
Targeting galectin-3 by natural glycosides: a computational approach
AbstractAs a carbohydrate-binding protein, galectin-3 represented as a potential target for numerous therapeutic inventions, as it controls cell proliferation, promotes inflammatory responses, inhibits apoptosis, and a negative regulator of memory formation. The regulations by galectin-3 can be blocked by the compounds having the multivalent presentation of carbohydrate (galactose) derivatives; therefore, the present study focused on the natural glycosides to find a potent inhibitor with reduced toxicity. Here, we introduced a computational pipeline by integrating molecular docking, steered molecular dynamics simulation an...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - January 27, 2020 Category: Bioinformatics Source Type: research
Two-dimensional finite element model to study the effect of periodic physical exercise on temperature distribution in peripheral regions of human limbs
AbstractThe human body regulates the body core temperature at a uniform temperature to maintain the structure and function of various physical and physiological processes. The physical exertion causes thermal stress which can disturb these mechanisms of thermoregulation under various environmental conditions and can lead to impairment of physiological functions. In view of the above, a finite element model has been developed to study thermal stress in peripheral regions of human limbs during periodic exercise and rest. It is assumed that the subject is doing exercise periodically by taking rest at regular intervals. The hu...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - January 13, 2020 Category: Bioinformatics Source Type: research
Sample size determination for biomedical big data with limited labels
In this study, we explore sample size determination methods for four real-world biomedical datasets, spanning genomics, proteomics, electronic health records, and insurance claims data, all with millions of instances each and<2% class ratio. The methods used involve approximating a learning curve for a large amount of data using a small amount of data. We evaluate an existing method that fits an inverse power law model to a small learning curve and introduce a novel semi-supervised method that utilizes the large amount of unlabeled data for estimating a learning curve. We find that the inverse power law method is applic...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - January 10, 2020 Category: Bioinformatics Source Type: research
ISCMF: Integrated similarity-constrained matrix factorization for drug –drug interaction prediction
AbstractDrug –drug interaction (DDI) prediction prepares substantial information for drug discovery. As the exact prediction of DDIs can reduce human health risk, the development of an accurate method to solve this problem is quite significant. Despite numerous studies in the field, a considerable number of DD Is are not yet identified. In the current study, we used Integrated Similarity-constrained matrix factorization (ISCMF) to predict DDIs. Eight similarities were calculated based on the drug substructure, targets, side effects, off-label side effects, pathways, transporters, enzymes, and indication d ata as well as ...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - January 9, 2020 Category: Bioinformatics Source Type: research
SL-GLAlign: improving local alignment of biological networks through simulated annealing
AbstractBiological networks are used to describe molecular machineries within cells. Therefore, the comparison among networks of different species or different states (e.g., healthy vs diseased people) may reveal relevant knowledge such as information about evolution. Comparison among networks is usually performed using network alignment algorithms. In a previous work, we used global network alignment to produce prior knowledge about networks that has been used on local network alignment algorithm. Here, we present Simulated Annealing-Global Local Aligner (SL-GLAlign), a novel framework methodology based on the use of topo...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - January 7, 2020 Category: Bioinformatics Source Type: research
Web Information Extraction for Finding Remedy Based on a Patient-Authored Text: A Study on Homeopathy
AbstractAutomatic medical diagnosis and remedy finding is an active research area for decades. The increasing trend of finding health remedies through the internet emerged the necessity of research on the analysis of the patient-authored text. Focussed analysis of the patient-authored text can also help in automatic remedy finding. As the web contains a huge amount of medicine and diagnosis-related information, an intelligent system can extract the relevant information to provide a health remedy given a patient-authored text query. In this paper, we attempted to develop such a system. As the patients ’ description of suf...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - January 7, 2020 Category: Bioinformatics Source Type: research
Multi-linear regression model, molecular binding interactions and ligand-based design of some prominent compounds against Mycobacterium tuberculosis
AbstractMultidrug-resistant strains ofMycobacterium tuberculosis still remain a major challenge in creating first-hand drugs for treating tuberculosis. Development and syntheses of novel compounds with more potent anti-tubercular agents are usually by the trial and error approach which is time consuming and expensive. QSAR is a theoretical approach which has the potential to reduce the aforementioned problem in discovering new potent drugs againstM. Tuberculosis. This approach was employed to develop the multivariate QSAR model to correlate the chemical structures of the 1,2,4-triazole analogues with their observed activit...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - January 6, 2020 Category: Bioinformatics Source Type: research
Retraction Note to: Regional patterning of co-expressed genes in autistic brains
The Editors-in-Chief have retracted this article because it is based on and significantly overlaps with an unpublished manuscript by Dr Mingqing Xu. Fereshteh Izadi disagrees with this retraction. (Source: Network Modeling Analysis in Health Informatics and Bioinformatics)
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - January 5, 2020 Category: Bioinformatics Source Type: research
Developing an effective biclustering technique using an enhanced proximity measure
AbstractThis paper introduces an enhanced version of Pearson ’s correlation coefficient (PCC) to achieve better biclustering-enabled co-expression analysis. The modified measure called local pearson correlation measure (LPCM) helps detect shifting, scaling, and shifting-and-scaling correlation patterns effectively over gene expression data in the presence o f outlier. An LPCM-based biclustering technique called local correlation-based biclustering technique (LCBT) has also been proposed to identify biclusters of high biological significance. The biclustering results have been established both statistically and biological...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - January 1, 2020 Category: Bioinformatics Source Type: research
Performance evaluation of classification methods with PCA and PSO for diabetes
AbstractDiabetes has become one of the major health concerns for the modern day population. This can be attributed to a number of factors such as unhealthy lifestyle, meager diet, genetics, obesity, etc. The rapid growth in the number of diabetic patients urges the requirement for a state-of-the-art healthcare against such diseases. Early prediction of such diseases can be very useful for mitigating the risks associated with such diseases. In this context, this research proposes an indigenous efficient diagnostic tool for the detection of diabetes. The proposed methodology comprises two phases: Phase-I deals with collectio...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - December 16, 2019 Category: Bioinformatics Source Type: research
A comparative study of features selection for skin lesion detection from dermoscopic images
AbstractMelanoma is rare and mainly considered as the dangerous category of skin cancer. Many researchers proposed diverse efficient techniques for melanoma detection. The main focus of this research is: (1) to discuss the traditional clinical methods for diagnosing skin cancer melanoma, and (2) to review the existing researcher ’s attempts in response the critical and challenging task is features selection and extraction for skin cancer melanoma detection from dermoscopy images. This research will also be helpful to recognize the research background of skin cancer melanoma detection through image processing techniques. ...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - December 16, 2019 Category: Bioinformatics Source Type: research
Using Twitter to raise the profile of childhood cancer awareness month
This study uses cross-sectional, descriptive-analytical methodology to explore how Twitter was employed during CCAM. We collected childhood cancer-related tweets from August 30 to October 2, 2015, which coincided with CCAM and several days before and after the awareness month. Using MALLET, we applied Latent Dirichlet allocation statistical modeling to extract the main topics of the collected tweets. We then explored how four different types of accounts —organizations, news agencies, celebrities, and individuals—used social media to talk about childhood cancer during CCAM using qualitative content analysis. Our researc...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - December 5, 2019 Category: Bioinformatics Source Type: research
