Bioinformatics Commons^™

Whole Genome And Reverse Protein Phase Array Landscapes Of Patient Derived Osteosarcoma Xenograft Models, Chia-Chin Wu, Licai Huang, Zhongting Zhang, Zhenlin Ju, Xingzhi Song, E Anders Kolb, Wendong Zhang, Jonathan Gill, Min Ha, Malcolm A Smith, Peter Houghton, Christopher L Morton, Raushan Kurmasheva, John Maris, Yael Mosse, Yiling Lu, Richard Gorlick, P Andrew Futreal, Hannah C Beird

Student and Faculty Publications

Osteosarcoma is the most common primary bone malignancy in children and young adults, and it has few treatment options. As a result, there has been little improvement in survival outcomes in the past few decades. The need for models to test novel therapies is especially great in this disease since it is both rare and does not respond to most therapies. To address this, an NCI-funded consortium has characterized and utilized a panel of patient-derived xenograft models of osteosarcoma for drug testing. The exomes, transcriptomes, and copy number landscapes of these models have been presented previously. This study now adds …

A Review Of How Bioinformatics And Genome Sequencing Are Affecting Precision Medicine, Taylor S. Hickey

Honors Theses

Advancement in genomic sequencing and bioinformatics methods have been affecting biomedical research through precision medicine, especially in the area of cancer. Vaccine therapies can be developed using neoantigens that target specific mutations in tumors. The goals of this research are to identify mutations that lead to cancer and then define subpopulations in which patients can easily be identified. The future goal is to have targeted vaccines that are specific to each subpopulation ready to be used in treatment of their cancer. Limitations to reaching these goals have been due to tumor heterogeneity, cancer location, and difficulty in creating neoantigens for …

The Genetics Of Skin Cancer: What Genes Drive The Development Of Basal Cell Carcinoma, Squamous Cell Carcinoma, And Melanoma?, Cassandra Poole, Abagail Pack, Elizabeth Whitehead, Virginia Marshall

Spring Showcase for Research and Creative Inquiry

Skin cancer is one of the most common forms of cancer worldwide. The American Academy of Dermatology estimates that 9500 people in the United States are diagnosed with skin cancer every day, and that 1 in 5 Americans will be diagnosed with skin cancer by age 70. With such a high prevalence of disease, understanding how skin cancer develops and how it can be treated is extremely important. This project aims to analyze the genes involved in the development of the three most common forms of skin cancer: basal cell carcinoma, squamous cell carcinoma, and melanoma.

A Machine Learning Framework For Identifying Molecular Biomarkers From Transcriptomic Cancer Data, Md Abdullah Al Mamun

FIU Electronic Theses and Dissertations

Cancer is a complex molecular process due to abnormal changes in the genome, such as mutation and copy number variation, and epigenetic aberrations such as dysregulations of long non-coding RNA (lncRNA). These abnormal changes are reflected in transcriptome by turning oncogenes on and tumor suppressor genes off, which are considered cancer biomarkers.

However, transcriptomic data is high dimensional, and finding the best subset of genes (features) related to causing cancer is computationally challenging and expensive. Thus, developing a feature selection framework to discover molecular biomarkers for cancer is critical.

Traditional approaches for biomarker discovery calculate the fold change for each …