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Thanks to the new positioning and information capture technologies; trajectory data which handle information related to moving objects can be captured and treated. This gave birth to a new data warehouse type called trajectory data warehouse that is essential to model and to implement to analyze and understand the nature and the behavior of movements of objects in various contexts. However, it is...
Complex biological systems are often represented as networks and studied computationally. In protein–protein interaction networks, interactions give rise to certain compounds known as protein complexes. Identifying functional protein complexes is an emerging field of study in system biology. Several machine learning methods have been proposed so far to detect functionally enriched protein complexes...
The advancements in sequencing high-throughput human genome and computational abilities have tremendously improved the understanding of the genetic architecture behind the complex diseases. The development of high-throughput genotyping and next-generation sequencing technologies enables large-scale data for genetic epidemiological analysis. These advances led to the identification of a number of single...
Artificial neural networks are one of the most efficient methods for pattern recognition and have a vast range of applications for aiding medical decision making. The proposed study applies feed-forward back-propagation neural networks as a classifier and compares the combination of nine learning algorithms and three activation functions to build a knowledge-based system with the best network architecture...
Semantic similarity measures (SSMs) are used to evaluate the similarity among terms of an ontology. Biological entities, e.g., gene products, are often annotated with terms extracted from existing ontologies. A common application is to find the similarity or dissimilarity among two entities through the application of SSMs to their annotations. More recently, researchers have introduced the semantic...
Nowadays, patients are often in a hurry to know their analysis and concise explanations their medical images pending the doctor’s decision. Most of the time, doctors can make mistakes leading to unpredictable damage in patients. In order to minimize medical errors by fostering collaboration between physicians and/or patients, we propose in this paper, as a first contribution, a medical social network...
A series of 47 indole-3-carboxamide derivatives with their renin inhibitors were subjected to QSAR to derive a correlation between biological activity as a dependent variable and various descriptors as independent variables. The best 2D-QSAR model having cross-validated squared correlation coefficient q2 = 0.7847 with external predictive of pred_r2 = 0.8193. Based on k-nearest neighbor method the...
We develop, present, and analyze a simple, new 2-approximation algorithm for block sorting in which we use a newly introduced combinatorial structure called an ordered pair. Our algorithm achieves the best known approximation ratio of 2 , the tightest known upper bound in terms of the number of block moves needed for block sorting.
Medical doctors and clinical technologists operate specific, complicated diagnostic systems to assess venous diseases. Instead of using such expensive equipment, low-cost infrared cameras can capture vein images noninvasively and simply. However, the recorded image has a possibility to result in low contrast and a low signal-to-noise (S/N) ratio. An effective image filtering method to estimate venous...
Prediction of epitope has great importance in the development of vaccine, drug and peptide libraries and immunologic research. There are very few methods for the prediction of patches containing conformational epitopes, and ninety percent of the epitopes are of conformational type. In this paper, an attempt has been made to propose soft support vector machine model based on the evaluation of different...
This article proposes a robust parametric identifier of systems that describe metabolic networks in microorganisms. This identifier implements a robust decentralized parallel differentiator that recovers the time variation of the concentrations of all the substances involved in the metabolic network. The sense of decentralized concept used in this study regards the application of the differentiator...
Malaria disease is caused by the transmission of Plasmodium, through the bite of a female Anopheles mosquito. Although the Plasmodium life-cycle has been extensively characterized, relatively little is known about sporozoite interaction with host organelles and proteins. Individuals that survive continuous exposure to infection do eventually develop clinical immunity, suggesting that a vaccine against...
S-adenosyl-l-homocysteine hydrolase of Plasmodium falciparum (PfSAHH) has been reported as a potential drug target against malaria. A series of aristeromycin derivatives and analogs were designed and tested for inhibition of PfSAHH. 2-Fluoroaristeromycin has been reported as a potential inhibitor of PfSAHH. Here, we have performed the molecular dynamics simulation study of 2-Fluoroaristeromycin with...
The study and systematic analysis of protein–protein interaction networks relevant to disease or well-being have become an integral part of systems biology. Recent studies have revealed strong association between the topological properties and biological function of proteins in networks. Hypoxia is a pathophysiological condition which arises due to low oxygen concentration in conditions like prenatal...
The significant role of long non-coding RNAs (lncRNAs) in various cellular functions, such as gene imprinting, immune response, embryonic pluripotency, tumorogenesis, and genetic regulations, has been widely studied and reported in recent years. Several experimental and computational methods involving genome-wide search and screenings of ncRNAs are being proposed utilizing sequence features-length,...
Online medical information prosumerism is supported by search engines, web sites, forums and social networks, all tools which provide a timely browsing of the big data of medical information. Reliable medical ecosystems require an assessment of such data, to control its quality from both clinical and patient standpoints. In addition, independent of its scientific accuracy, the full gamut of human...
An in silico study was conducted to identify antigens with potential possibility of being a vaccine against type 1 diabetes mellitus (T1DM). A molecular mimicry between protein 2C of coxsackievirus B4 and autoantigen glutamic acid decarboxylase 65 is a significant factor in the pathogenesis of T1DM. The aim of this study was to predict the protein 2C of coxsackievirus B4 epitopes and design a vaccine...
Infectious diseases are an important cause of fatality worldwide and administration of vaccines could provide long-lasting protection against responsible infection. Incorporating of adjuvants to vaccine formulations can enhance the effectiveness of antigens. This study proposes an in silico approach for designing of some flagellin derivatives as adjuvant candidates and investigation of their interaction...
Distinguishing migraine from stroke is a challenge due to many common signs and symptoms. It is important to consider the cost of hospitalization and the time spent by neurologists and stroke nurses to visit, diagnose, and assign appropriate care to the patients; therefore, devising new ways to distinguish stroke, migraine and other types of mimics can help in saving time and cost, and improve decision-making...
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