A Bioinformatics Tool for Identifying Intratumoral Microbes from the ORIEN Dataset.

Cankun Wang Anjun Ma Yingjie Li Megan E McNutt Shiqi Zhang Jiangjiang Zhu Rebecca Hoyd Caroline E Dravillas Lary A Robinson Carlos H F Chan Yousef Zakharia Rebecca D Dodd Cornelia M Ulrich Sheetal Hardikar Michelle L Churchman Ahmad A Tarhini Eric A Singer Alexandra P Ikeguchi Martin D McCarter Nicholas C Denko Gabriel Tinoco Marium Husain Ning Jin Afaf E G Osman Islam El Jilany Aik Choon Tan Samuel S Coleman Louis Denko Gregory M Riedlinger Bryan Paul Schneider Daniel J Spakowicz Qin Manull null

Published in: Cancer research communications (2024)

Studying the tumor microbiome in high-throughput sequencing data is challenging because of the extremely sparse data matrices, heterogeneity, and high likelihood of contamination. We present a new deep learning tool, MEGA, to refine the organisms that interact with tumors.

Keyphrases

high throughput sequencing
deep learning
electronic health record
big data
risk assessment
single cell
artificial intelligence
machine learning
convolutional neural network
health risk
climate change
multidrug resistant