Engineering Commons^™

Discovering Gene Functional Relationships Using Faun (Feature Annotation Using Nonnegative Matrix Factorization), Elina Tjioe, Michael W. Berry, Ramin Homayouni

Faculty Publications and Other Works -- EECS

Background

Searching the enormous amount of information available in biomedical literature to extract novel functional relationships among genes remains a challenge in the field of bioinformatics. While numerous (software) tools have been developed to extract and identify gene relationships from biological databases, few effectively deal with extracting new (or implied) gene relationships, a process which is useful in interpretation of discovery-oriented genome-wide experiments.

Results

In this study, we develop a Web-based bioinformatics software environment called FAUN or Feature Annotation Using Nonnegative matrix factorization (NMF) to facilitate both the discovery and classification of functional relationships among genes. Both the computational complexity …

Graph Algorithms For Machine Learning: A Case-Control Study Based On Prostate Cancer Populations And High Throughput Transcriptomic Data, Gary L. Rogers, Pablo Moscato, Michael A. Langston

Faculty Publications and Other Works -- EECS

Background

The continuing proliferation of high-throughput biological data promises to revolutionize personalized medicine. Confirming the presence or absence of disease is an important goal. In this study, we seek to identify genes, gene products and biological pathways that are crucial to human health, with prostate cancer chosen as the target disease.

Materials and methods

Using case-control transcriptomic data, we devise a graph theoretical toolkit for this task. It employs both innovative algorithms and novel two-way correlations to pinpoint putative biomarkers that classify unknown samples as cancerous or normal.

Results and conclusion

Observed accuracy on real data suggests that we are …

Developing Chitosan-Based Biomaterials For Brain Repair And Neuroprosthetics, Zheng Cao

Masters Theses

Chitosan is widely investigated for biomedical applications due to its excellent properties, such as biocompatibility, biodegradability, bioadhesivity, antibacterial, etc. In the field of neural engineering, it has been extensively studied in forms of film and hydrogel, and has been used as scaffolds for nerve regeneration in the peripheral nervous system and spinal cord. One of the main issues in neural engineering is the incapability of neuron to attach on biomaterials. The present study, from a new aspect, aims to take advantage of the bio-adhesive property of chitosan to develop chitosan-based materials for neural engineering, specifically in the fields of brain …