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Description:: Annual age-adjusted breast cancer incidence rates in the United States have been static for decades. More recently, the development of massively parallel, high throughput DNA sequencing has enabled the cataloging of somatic mutations in cancer. Mutations are non-random and occur within sequence motifs. These motifs provide us with evidence to...
Keyword:: Natural Language Processing, Electronic Health Records, Genomics, Mutational Processes, Breast Cancer, and Machine Learning
Subject:: Bioinformatics and Computer science
Creator:: Zeng, Zexian
Owner:: Scholarly Digital Publishing
Language:: en
Date Uploaded:: 02/12/2020
Date Created:: 2019-01-01
Resource Type:: Dissertation
Alternate Identifier:: http://dissertations.umi.com/northwestern:14500 and etdadmin_upload_635668

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