Open Access. Powered by Scholars. Published by Universities.®

Bioinformatics Commons

Open Access. Powered by Scholars. Published by Universities.®

Articles 1 - 2 of 2

Full-Text Articles in Bioinformatics

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 Oct 2022

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 Mar 2022

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 …