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Single Nuclear Polymorphisms (SNPs) are the majority of genetic variations occurring in a genome and help in understanding the genetics behind many complex diseases. By knowing the function of SNPs, the human phenotypic variations can be well known. Identification of functional SNPs in a disease-related gene is still a challenge. In this work, using computational methods, we have analyzed the genetic...
In this paper, we describe an integrated framework which incorporates data mining and statistical methods leading to the development of a visualization tool to facilitate users in understanding and exploring health indicator data. Due to the increasing cost of providing health care and decreasing participation in physical activities, motivating individuals to self-monitor themselves and according...
Bioinformatics has become intrinsic to modern genomics research. All genomics studies, viz., structural, functional and comparative genomics research, integrate bioinformatics with experimental components. Current bioinformatics facilities and computational capabilities will enable the generation of hypotheses and stimulate the annotation and functional discoveries for new gene and genomes. The resulting...
Binding of Major histocompatibility complex (MHC) peptide is a prerequisite for T cell activation in the immune system. MHC-binding peptides have shown promising results for immunodiagnostics and immunotherapeutic purposes. HLA-B*2705 is found to be associated with the development of variety of autoimmune diseases including Ankylosing spondylitis. Detecting MHC class I allele HLA-B*2705 binding peptides...
Non-small cell lung cancer today has several reported testimonies of aberrant promoter hypermethylation of tumor suppressing genes. In this study, a group of five genes (CDKN2A, APC, MGMT, DAPK and RASSF1) have been evaluated, using epigenetic tools and techniques to investigate their frequency of hypermethylation, prediction of CpG islands and expected primers along with their phylogenetic relationships...
Amprenavir is an HIV-1 protease inhibitor (PI) that has recently been approved for the treatment HIV/AIDS. Despite its outstanding safety and efficacy, site-specific mutations occurring at one or more residues in HIV-1 protease have caused the development of resistance to PI. Unfortunately, a comprehensive understanding of the resistance mechanisms is still lacking. Therefore, the present investigation...
A medical report contains many elements such as medical images accompanied by text descriptions. We present in this paper a new approach for semantic automatic annotation of medical images. The proposed approach uses the bag of words model to represent the visual content of the medical image combined with text descriptors based on term frequency–inverse document frequency technique and reduced by...
Local sequence alignment (LSA) is an essential part of DNA sequencing. LSA helps to identify the facts in biological identity, criminal investigations, disease identification, drug design and research. Large volume of biological data makes difficulties to the performance of efficient analysis and proper management of data in small space has become a serious issue. We have subdivided the data sets...
In this paper, we have attempted to build multilayer perceptron (MLP) and support vector machine (SVM) models for predicting survivability of the oral cancer patients who visit the ENT OPD. MLP and SVM have been applied in the past by few researchers for prediction of oral cancer using the genetic database. However, the database used for current research has the attributes like clinical symptoms,...
Clustering of genes on the basis of expression profiles is generally the first step in understanding how a class of genes behaves in a biological process. A number of supervised and unsupervised algorithms are available in statistics and machine learning literature for clustering microarray data, but the algorithms are restricted in their ability to evaluate the results of a clustering algorithm in...
It is now recognized that genetic interactions (epistasis) are important sources of the hidden genetic variations and may play an important role in complex diseases. Identifying genetic interactions not only helps to explain part of the heritability of complex diseases, but also provides the clue to understand the underlying pathogenesis of complex diseases. Advances in high-throughput technologies...
Long non-coding RNAs (lncRNAs) have been implicated in various biological processes, and are linked in many dysregulations. Over the past decade, researchers reported a large number of human disease associations with the lncRNAs, both intergenic lncRNAs (lincRNAs) and non-intergenic lncRNAs. Thanks to the next generation sequencing platform, RNA-seq, through which researchers also were able to quantify...
Gene regulatory networks inference from gene expression data is an important problem in systems biology field, in which the main goal is to comprehend the global molecular mechanisms underlying diseases for the development of medical treatments and drugs. This problem involves the estimation of the gene dependencies and the regulatory functions governing these interactions to provide a model that...
Machine learning can be broadly divided into supervised and unsupervised learning (Hastie et al. in The elements of statistical learning, Springer, New York, 2009). In supervised learning which is also known as classification, a classifier learns from some objects with known class labels and later assigns class labels to unknown objects based on acquired knowledge (Kotsiantis et al. in Proceedings...
A variety of adverse outcomes, such as kidney injury, death, cardiac injury, and respiratory failure affect a significant number of patients after surgery. Previous research has investigated possible predictors for these outcomes, including features extracted from physiologic time series, change points in the time series, and prior conditions. This study builds upon this previous work by further exploring...
Molecular and soft bio-molecular biometrics are an advancing field that involves the analysis of a person’s unique biological markers at a molecular level to ascertain identity. Bacteria communities found on the skin of the human hand have shown to be highly diverse and to have a low percentage of similarity between individuals. The goal of this research effort is to see if a person’s demographics,...
One of the main problems in treating stroke patients is accurate and timely triage and assessment. Not all stroke events have direct severe consequences. Full strokes are often preceded by transient ischemic attacks (TIA) or mini strokes, which exhibit signs and symptoms similar to less concerning health events, e.g., migraines. In this paper, natural language techniques are presented to process a...
In this paper, we introduce a personalized parameterization approach, namely prep-g, to explore impact of gene expression values from breast cancer patients on tumor growth and shrinkage characteristics using xenograft models. In construction of prep-g parameterization, in addition to individual effects of the breast cancer-related gene expressions, the impact of the correlation among them and the...
Data mining using association rule is widely applied in medicine, particularly in cancer epidemiology. It is reported that this technique has certain uncertainty. To minimize the uncertainty, fuzzy logic is used with association rules. To demonstrate the efficiency of these methods further, geographical information system tool is used to spatially view results obtained from above-mentioned techniques...
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