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Articles 1 - 3 of 3
Full-Text Articles in Genetics and Genomics
Leveraging Global Gene Expression Patterns To Predict Expression Of Unmeasured Genes, James Rudd, René A. Zelaya, Eugene Demidenko, Ellen L. Goode, Casey S. Greene S. Greene, Jennifer A. Doherty
Leveraging Global Gene Expression Patterns To Predict Expression Of Unmeasured Genes, James Rudd, René A. Zelaya, Eugene Demidenko, Ellen L. Goode, Casey S. Greene S. Greene, Jennifer A. Doherty
Dartmouth Scholarship
BackgroundLarge collections of paraffin-embedded tissue represent a rich resource to test hypotheses based on gene expression patterns; however, measurement of genome-wide expression is cost-prohibitive on a large scale. Using the known expression correlation structure within a given disease type (in this case, high grade serous ovarian cancer; HGSC), we sought to identify reduced sets of directly measured (DM) genes which could accurately predict the expression of a maximized number of unmeasured genes.
Integrative Analysis Of Survival-Associated Gene Sets In Breast Cancer, Frederick S. Varn, Matthew H. Ung, Shao Ke Lou, Chao Cheng
Integrative Analysis Of Survival-Associated Gene Sets In Breast Cancer, Frederick S. Varn, Matthew H. Ung, Shao Ke Lou, Chao Cheng
Dartmouth Scholarship
Patient gene expression information has recently become a clinical feature used to evaluate breast cancer prognosis. The emergence of prognostic gene sets that take advantage of these data has led to a rich library of information that can be used to characterize the molecular nature of a patient’s cancer. Identifying robust gene sets that are consistently predictive of a patient’s clinical outcome has become one of the main challenges in the field. We inputted our previously established BASE algorithm with patient gene expression data and gene sets from MSigDB to develop the gene set activity score (GSAS), a metric that …
Systems Level Analysis Of Systemic Sclerosis Shows A Network Of Immune And Profibrotic Pathways Connected With Genetic Polymorphisms, J. Matthew Mahoney, Jaclyn Taroni, Viktor Martyanov, Tammara A. A. Wood, Casey S. Greene, Patricia A. Pioli, Monique E. Hinchcliff, Michael L. Whitfield
Systems Level Analysis Of Systemic Sclerosis Shows A Network Of Immune And Profibrotic Pathways Connected With Genetic Polymorphisms, J. Matthew Mahoney, Jaclyn Taroni, Viktor Martyanov, Tammara A. A. Wood, Casey S. Greene, Patricia A. Pioli, Monique E. Hinchcliff, Michael L. Whitfield
Dartmouth Scholarship
Systemic sclerosis (SSc) is a rare systemic autoimmune disease characterized by skin and organ fibrosis. The pathogenesis of SSc and its progression are poorly understood. The SSc intrinsic gene expression subsets (inflammatory, fibroproliferative, normal-like, and limited) are observed in multiple clinical cohorts of patients with SSc. Analysis of longitudinal skin biopsies suggests that a patient's subset assignment is stable over 6-12 months. Genetically, SSc is multi-factorial with many genetic risk loci for SSc generally and for specific clinical manifestations. Here we identify the genes consistently associated with the intrinsic subsets across three independent cohorts, show the relationship between these genes …