Deep learning for cancer type classification and driver gene identification

Background: Genetic information is becoming more readily available and is increasingly being used to predict patient cancer types as well as their subtypes. Most classification methods thus far utilize somatic mutations as independent features for classification and are limited by study power. We ai...

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Bibliographic Details
Main Authors:	Clare, S.E (Author), Khan, S.A (Author), Li, X. (Author), Luo, Y. (Author), Mao, C. (Author), Nugent, J.O (Author), Vo, A. (Author), Zeng, Z. (Author)
Format:	Article
Language:	English
Published:	BioMed Central Ltd 2021
Subjects:	Cancer Classification Classification (of information) Convolution Convolutional neural network Convolutional neural networks Deep learning Deep Learning Diseases DNA sequence DNA sequences DNA Sequencing Forecasting Gene encoding genetics Germline Germline variant Germline variants human Humans Insertions and deletions neoplasm Neoplasms Novel methods oncogene Oncogenes Power Sequence Analysis, DNA Somatic mutation Type predictions whole exome sequencing Whole Exome Sequencing Whole-exome sequencing
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Deep learning for cancer type classification and driver gene identification

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