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Bioinformatics research is characterized by voluminous and incremental datasets and complex data analytics methods. The machine learning methods used in bioinformatics are iterative and parallel. These methods can be scaled to handle big data using the distributed and parallel computing technologies. Usually big data tools perform computation in batch mode and are not optimized for iterative processing...
Medical social networking sites have enabled multimedia content sharing in large volumes by allowing physicians and patients to upload their medical images. Moreover, it is necessary to employ new techniques to effectively handle and benefit from them. This huge volume of images needs to formulate new types of queries that pose complex questions to medical social network databases. Content-based image...
Network-based approaches to human disease have diverse biological and clinical applications. A more appropriate interpretation of biological interconnectivity with disease progression could possibly lead to identification of disease pathways and disease genes. This, in turn, helps in accurate prediction of biomarkers and targets for drug development. This study is a large-scale system-level network...
Glaucoma is a chronic eye disease that causes blindness. It is the one of the most common causes of blindness in the world. It results in the loss of vision which cannot be regained. Although glaucoma is not curable, detection of the disease in proper time can stop its further progression. The optic disk (OD), optic cup (OC) and neuroretinal rim (NRR) constitute the important features in a retinal...
Microbial glutaminase has been extensively used as antitumor drug in pharmaceutical industry from past few decades. The structural analysis based on homology modeling predicted a hypothetical 3D model structure for l-glutaminase from Bacillus cereus MTCC 1305 using peptide sequence data obtained from MALDI-TOF MS and template model of X-ray crystal structure of l-glutaminase from Bacillus subtilis...
With the high prevalence of autism spectrum disorder (ASD) among the younger generation, there is a shortage of adequate resources to deliver care for the individuals dealing with autism. Families dealing with autism face huge economic costs and emotional stress to provide care for personnel diagnosed with ASD. Globally almost two billion people use social media regularly. Social media have many advantages...
A system can be defined as an organized, interconnected structure consisting of interrelated and interdependent elements (e.g., components, factors, members, parts). These parts and processes are connected by structural and/or behavioral relationships and continually influence one another directly or indirectly to maintain a balance essential for the existence of the system, and for achieving its...
The advancements in genetic epidemiology have focused more on understanding the associations and functional relationships among the genes. Identifying the susceptible genes and their interaction effects over the complex traits remains statistically and computationally challenging. An associative classification-based multifactor dimensionality reduction method (MDRAC) was proposed to improve the identification...
To improve their knowledge of diseases, physicians need to study and learn from their patients and from their related medical records. Physicians continue to initiate this learning process by taking into account the history of the patient’s medical problems and physical examination findings in the patient’s medical record, which illustrates the importance of medical and health care databases. In other...
We consider the problem of adding a large unlabeled sample from the target domain to boost the performance of a domain adaptation algorithm when only a small set of labeled examples is available from the target domain. In particular, we consider the problem setting motivated by the tasks of splice site prediction and protein localization. For example, for splice site prediction, annotating a genome...
The present work was carried out to design and develop novel protein kinase casein kinase 2 inhibitors of benzimidazole derivatives using 2D-QSAR, 3D-QSAR, and pharmacophore modeling. The pharmacophore models were observed to be in good correlation with 2D-QSAR and 3D-QSAR predicted activities and had the correlation coefficients (r2) of 0.7832 and 0.7483, respectively. The activities predicted by...
Glaucoma is a group of disease characterized by progressive optic nerve degeneration and retinal ganglion cells (RGCs). The RGCs and evaluation elevated intraocular pressure are the most common cause for glaucoma. In this study, RGC death pathway of glaucoma was modeled to predict the response of the protein receptor, ligand, inhibitor and other regulatory units, which are involved in RGC death pathway...
Medical social networking sites enabled multimedia content sharing in large volumes, by allowing physicians and patients to upload their medical images. These images are diagnosed and commented, in different languages, by several specialists instantly. Moreover, it is necessary to employ new techniques, in order to automatically extract information and analyze knowledge from the huge number of comments...
Machine learning studies automatic algorithms that improve themselves through experience. It is widely used for analyzing and extracting value from large biomedical data sets, or “big biomedical data,” advancing biomedical research, and improving healthcare. Before a machine learning model is trained, the user of a machine learning software tool typically must manually select a machine learning algorithm...
2D quantitative structure–activity relationships (2D QSAR) studies were performed on a series of diarylcyclopentene derivatives as prostaglandin EP1 receptor antagonist. To establish the relationship between Prostaglandin EP1 receptor and diarylcyclopentene derivatives, a 2D-QSAR model based on individual, estate numbers, structural, electro topological and baumann alignment descriptors parameters...
Metabolic pathways can be conceptualized as the biological equivalent of a data pipeline. In living cells, series of chemical reactions are carried out by different proteins called enzymes in a stepwise manner. However, many pathways remain incompletely characterized, and in some of them, not all enzyme components have been identified. Kernel methods are useful in many difficult problem areas, such...
Microbial interactions and relationships are significant for animals, insects and plants. Metagenomic research enables properassessments and analysis for microbial organs and communities. The analysis helps to gain detailed insights on miscopies insects. Recent machine learning techniques focused on algorithms and data mining tools to check the depth of interactions and relationships on metagenomic...
Digital Health Social Networks (DHSNs) are common; however, there are few metrics that can be used to identify participation inequality. The objective of this study was to investigate whether the Gini coefficient, an economic measure of statistical dispersion traditionally used to measure income inequality, could be employed to measure DHSN inequality. Quarterly Gini coefficients were derived from...
In this study, QSAR modeling was performed for predicting the IC50 value for a set of HIV-1 integrase inhibitors using multiple regression and partial least square method obtaining an optimized model for each method. These models were used to predict a set of test compounds obtained by performing a chemical similarity search of the training set from the NCBI PubChem database subjected to the Lipinski...
In the present study, two/three-dimensional quantitative structure activity relationship models using 2D QSAR and pharmacophore approaches were developed for a series of benzimidazole derivatives as angiotensin II receptor AT1 receptor antagonists. The 2D QSAR model was developed using partial least square analysis in VLife MDS and helps in identifying the descriptors. The best 2D QSAR equation has...
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