The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In this work, we propose a novel genetic pathway discovery and comparison analysis framework integrating newly generated gene expression microarray data and existing biological pathway information. Starting with the significance analysis of microarray (SAM), a list of differentially expressed genes among groups is obtained. This gene list is then imported to the Ingenuity Pathway Analysis (IPA) to...
Complex diseases may be caused by interactions or combined effects between multiple genetic and environmental factors. One of the main limitations of testing for interaction between genetic loci in large whole genome studies is the high computational cost of performing such analyses. In this study a new methodology for interaction testing (commonly referred to in genetics as the epistatic effect)...
Schizophrenia, Alzheimer's disease, Parkinson's disease, and other neuropsychiatric degenerative disorders and dementias impose an enormous economic and psychosocial burden on society, communities, and families. In order to gain a better understanding of gene-brain-behavior relationships, improve treatment, and find cures for these diseases, translational research must be conducted with clinical trials...
Cardiovascular disease is the second most prevalent cause of morbidity and mortality in women of developed countries. Although it is well established that gender is a risk factor for cardiovascular disease, most gene expression analysis studies favour the identification of disease bio-markers and potential drug targets over combined populations. This study integrates genomic and systems approaches...
Cartilage damage is difficult to repair,as a major stimulator of matrix synthesis in cartilage, insulin-like growth factor I (IGF-I) is likely to play a important role in the process of repairing cartilage damage. To study the in vivo therapeutic effect of chitosan mediate igf-lgene transfection on repairing articular cartilage defect in rabbits.Chitosan-DNA nanoparticlesCS/igf-1 were prepared following...
One of the principal features of DNA microarrays is the volume of quantitative data that they generate. As a result, the major challenges in the field are how to handle, interpret and make use of these data. Currently, there are a large number of tools available which perform statistical analysis for constructing a significant gene set from the microarray data. There are others who given a set of...
The study of the genetic causes of disease is entering a new era. Variations in DNA sequence between individuals at a single position (locus) within the human genome are termed single nucleotide polymorphisms (SNPs), and may lead to a frank disease state or a variation in normal physiology. By comparing and contrasting the genomes of people who have a disease with the genomes of people who don't,...
This paper describes an interactive data exploration system for molecular and clinical data in the field of personalized medicine. It addresses the essential but to date unsolved problem of how to identify connections between genetic variants and their corresponding diseases or the response to certain drugs and treatments, respectively. It is therefore necessary to connect genetic with clinical data...
Both correct and harmonic expression of genes became an important factor of health care development. Genes expression changes are consider to be a reason of many diseases. Early detection of mentioned above changes allow for application of common treatment procedures before the first symptom are observed. Statistical methods applied for those purposes allow relatively simple selection of patients...
When analyzing the results of microarray experiments, biologists generally use unsupervised categorization tools. However, such tools regard each time point as an independent dimension and utilize the euclidean distance to compute the similarities between expressions. Furthermore, some of these methods require the number of clusters to be determined in advance, which is clearly impossible in the case...
A computational framework is presented for surface based morphometry to localize shape changes between groups of 3D objects. It employs the spherical harmonic (SPHARM) method for surface modeling and random field theory (RFT) for statistical inference. Several new components are introduced to overcome previous limitations: (1) a general linear model is used to facilitate controlling for covariates;...
RNA viruses like HIV and HCV have an extraordinary evolutionary potential to escape from both immune pressures and targeted drug therapies. In HIV infections, the emergence of drug resistant strains is of particular interest, as it complicates the choice of an optimal follow-up regimen. A series of bioinformatics tools for predicting drug resistance were previously developed to support physicians...
When analyzing biological data sets, a common approach is to partition the data into clusters. Examples of this include finding a subset of genes with co-regulated expression among experiments, grouping similar disease phenotypes, or implicating regions of genetic variation in disease. The ability to separate the data into subsets depends upon the structure of the distribution of points and the choice...
Genome-wide association study for complex diseases will generate massive amount of single nucleotide polymorphisms (SNPs) data. Univariate statistical test (i.e. Fisher exact test) was used to single out non-associated SNPs. However, the disease-susceptible SNPs may have little marginal effects in population and are unlikely to retain after the univariate tests. Also, model-based methods are impractical...
For the critical task of gene module discovery in genomic research, we present a model-based hierarchical data clustering and visualization algorithm, visual statistical data analyzer (VISDA), which effectively exploits human-data interaction to improve the clustering outcome. Guided by a diagnostic tree, we apply VISDA to a muscular dystrophy dataset that contains a number of different phenotypic...
A latent-threshold model and misclassification algorithm were implemented to examine potential misdiagnosis among 16 Alzheimer's disease (AD) subjects using gene expression data. Results obtained without invoking the misclassification algorithm showed limited predictive power of the model. When the misclassification algorithm was invoked, four subjects were identified as being potentially misdiagnosed...
Genome-wide association study for complex diseases will generate massive amount of single nucleotide polymorphisms (SNPs) data. Univariate statistical test (i.e. Fisher exact test) was used to single out non-associated SNPs. However, the disease-susceptible SNPs may have little marginal effects in population and are unlikely to retain after the univariate tests. Also, model-based methods are impractical...
A latent-threshold model and misclassification algorithm were implemented to examine potential misdiagnosis among 16 Alzheimer's disease (AD) subjects using gene expression data. Results obtained without invoking the misclassification algorithm showed limited predictive power of the model. When the misclassification algorithm was invoked, four subjects were identified as being potentially misdiagnosed...
For the critical task of gene module discovery in genomic research, we present a model-based hierarchical data clustering and visualization algorithm, visual statistical data analyzer (VISDA), which effectively exploits human-data interaction to improve the clustering outcome. Guided by a diagnostic tree, we apply VISDA to a muscular dystrophy dataset that contains a number of different phenotypic...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.