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Faculty Scholarship for the College of Science & Mathematics

Series

2013

Humans

Articles 1 - 3 of 3

Full-Text Articles in Life Sciences

Integrating Human Omics Data To Prioritize Candidate Genes., Yong Chen, Xuebing Wu, Rui Jiang Dec 2013

Integrating Human Omics Data To Prioritize Candidate Genes., Yong Chen, Xuebing Wu, Rui Jiang

Faculty Scholarship for the College of Science & Mathematics

BACKGROUND: The identification of genes involved in human complex diseases remains a great challenge in computational systems biology. Although methods have been developed to use disease phenotypic similarities with a protein-protein interaction network for the prioritization of candidate genes, other valuable omics data sources have been largely overlooked in these methods.

METHODS: With this understanding, we proposed a method called BRIDGE to prioritize candidate genes by integrating disease phenotypic similarities with such omics data as protein-protein interactions, gene sequence similarities, gene expression patterns, gene ontology annotations, and gene pathway memberships. BRIDGE utilizes a multiple regression model with lasso penalty to …


Identifying Potential Cancer Driver Genes By Genomic Data Integration., Yong Chen, Jingjing Hao, Wei Jiang, Tong He, Xuegong Zhang, Tao Jiang, Rui Jiang Dec 2013

Identifying Potential Cancer Driver Genes By Genomic Data Integration., Yong Chen, Jingjing Hao, Wei Jiang, Tong He, Xuegong Zhang, Tao Jiang, Rui Jiang

Faculty Scholarship for the College of Science & Mathematics

Cancer is a genomic disease associated with a plethora of gene mutations resulting in a loss of control over vital cellular functions. Among these mutated genes, driver genes are defined as being causally linked to oncogenesis, while passenger genes are thought to be irrelevant for cancer development. With increasing numbers of large-scale genomic datasets available, integrating these genomic data to identify driver genes from aberration regions of cancer genomes becomes an important goal of cancer genome analysis and investigations into mechanisms responsible for cancer development. A computational method, MAXDRIVER, is proposed here to identify potential driver genes on the basis …


Detection And Quantification Of Methylation In Dna Using Solid-State Nanopores., Jiwook Shim, Gwendolyn I Humphreys, Bala Murali Venkatesan, Jan Marie Munz, Xueqing Zou, Chaitanya Sathe, Klaus Schulten, Farhad Kosari, Ann M Nardulli, George Vasmatzis, Rashid Bashir Mar 2013

Detection And Quantification Of Methylation In Dna Using Solid-State Nanopores., Jiwook Shim, Gwendolyn I Humphreys, Bala Murali Venkatesan, Jan Marie Munz, Xueqing Zou, Chaitanya Sathe, Klaus Schulten, Farhad Kosari, Ann M Nardulli, George Vasmatzis, Rashid Bashir

Faculty Scholarship for the College of Science & Mathematics

Epigenetic modifications in eukaryotic genomes occur primarily in the form of 5-methylcytosine (5 mC). These modifications are heavily involved in transcriptional repression, gene regulation, development and the progression of diseases including cancer. We report a new single-molecule assay for the detection of DNA methylation using solid-state nanopores. Methylation is detected by selectively labeling methylation sites with MBD1 (MBD-1x) proteins, the complex inducing a 3 fold increase in ionic blockage current relative to unmethylated DNA. Furthermore, the discrimination of methylated and unmethylated DNA is demonstrated in the presence of only a single bound protein, thereby giving a resolution of a single …