Related Experiment Video
Updated: Jun 4, 2026
07:35
Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
Published on: October 11, 2018
GeneRanker: An Online System for Predicting Gene-Disease Associations for Translational Research
Graciela Gonzalez1, Juan C Uribe, Brock Armstrong
1Arizona State University, Tempe, AZ;
Summit on Translational Bioinformatics
|February 25, 2011
Summary
GeneRanker is a new online tool that helps researchers find relevant genes for diseases. It ranks genes by analyzing gene-disease links and protein interactions, improving research accuracy.
Area of Science:
- Bioinformatics
- Genomics
- Systems Biology
Background:
- The vast amount of genomic and molecular data presents challenges for researchers in identifying relevant genes.
- Efficiently refining searches for disease-associated genes requires advanced computational tools.
Purpose of the Study:
- To introduce GeneRanker, an online system designed to rank genes associated with specific diseases or biological processes.
- To provide researchers with a tool that integrates gene-disease associations and protein-protein interactions for improved accuracy.
Main Methods:
- GeneRanker combines gene-disease associations with protein-protein interaction data.
- It utilizes computational analysis of protein network topology to rank predicted gene associations.
- The system extracts interaction data from scientific literature.
Main Results:
- GeneRanker successfully generated ranked lists of potentially relevant genes.
- The system's performance was evaluated in the context of brain cancer research.
- The tool demonstrated the ability to refine gene prioritization based on network analysis.
Conclusions:
- GeneRanker offers a valuable bioinformatics solution for navigating complex genomic data.
- The system enhances the identification of disease-related genes by integrating diverse biological information.
- GeneRanker is freely accessible online, supporting broader research applications.
Related Concept Videos
01:11Genome-wide Association Studies-GWAS
Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
GWAS does not require the identification of the target gene involved in...
01:29Pharmacogenomics: Identification of New Drug Targets
Advances in genomics have profoundly influenced drug discovery by increasing both the speed and accuracy of pharmaceutical development. Pharmacogenomics, which examines how genetic variation influences drug response, facilitates the identification of novel therapeutic targets and enables patient stratification for personalized treatment. These strategies contribute to improved drug efficacy, minimized adverse effects, and more efficient clinical trial design.Mapping genetic differences...
02:46Genetic Screens
Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
Forward genetic screens
Forward or “classical” genetic screens involve creating random mutations in an organism’s DNA using radiation, mutagens, or insertion of additional bases, which result in visible changes...
Forward genetic screens
Forward or “classical” genetic screens involve creating random mutations in an organism’s DNA using radiation, mutagens, or insertion of additional bases, which result in visible changes...