Genetics and Genomics Commons^™

Droid: The Drosophila Interactions Database, A Comprehensive Resource For Annotated Gene And Protein Interactions, Jingkai Yu, Svetlana Pacifico, Guozhen Liu, Russell L. Finley Jr

Wayne State University Associated BioMed Central Scholarship

Abstract

Background

Charting the interactions among genes and among their protein products is essential for understanding biological systems. A flood of interaction data is emerging from high throughput technologies, computational approaches, and literature mining methods. Quick and efficient access to this data has become a critical issue for biologists. Several excellent multi-organism databases for gene and protein interactions are available, yet most of these have understandable difficulty maintaining comprehensive information for any one organism. No single database, for example, includes all available interactions, integrated gene expression data, and comprehensive and searchable gene information for the important model organism, Drosophila melanogaster. …

Mcm-Test: A Fuzzy-Set-Theory-Based Approach To Differential Analysis Of Gene Pathways, Lily R. Liang, Vinay Mandal, Yi Lu, Deepak Kumar

Wayne State University Associated BioMed Central Scholarship

Abstract

Background

Gene pathway can be defined as a group of genes that interact with each other to perform some biological processes. Along with the efforts to identify the individual genes that play vital roles in a particular disease, there is a growing interest in identifying the roles of gene pathways in such diseases.

Results

This paper proposes an innovative fuzzy-set-theory-based approach, Multi-dimensional Cluster Misclassification test (MCM-test), to measure the significance of gene pathways in a particular disease. Experiments have been conducted on both synthetic data and real world data. Results on published diabetes gene expression dataset and a list …

Fm-Test: A Fuzzy-Set-Theory-Based Approach To Differential Gene Expression Data Analysis, Lily R. Liang, Shiyong Lu, Xuena Wang, Yi Lu, Vinay Mandal, Dorrelyn Patacsil, Deepak Kumar

Wayne State University Associated BioMed Central Scholarship

Abstract

Background

Microarray techniques have revolutionized genomic research by making it possible to monitor the expression of thousands of genes in parallel. As the amount of microarray data being produced is increasing at an exponential rate, there is a great demand for efficient and effective expression data analysis tools. Comparison of gene expression profiles of patients against those of normal counterpart people will enhance our understanding of a disease and identify leads for therapeutic intervention.

Results

In this paper, we propose an innovative approach, fuzzy membership test (FM-test), based on fuzzy set theory to identify disease associated genes from microarray …