1. G2Vec: Distributed gene representations for identification of cancer prognostic genes
- Author
-
Jonghwan Choi, Ilhwan Oh, Jaegyoon Ahn, and Sangmin Seo
- Subjects
0301 basic medicine ,Carcinoma, Hepatocellular ,Computer science ,0206 medical engineering ,lcsh:Medicine ,Feature selection ,02 engineering and technology ,Computational biology ,Article ,03 medical and health sciences ,Text mining ,Deep Learning ,Neoplasms ,medicine ,Biomarkers, Tumor ,Humans ,Word2vec ,Gene Regulatory Networks ,lcsh:Science ,Gene ,Multidisciplinary ,business.industry ,Deep learning ,Gene Expression Profiling ,lcsh:R ,Cancer ,Computational Biology ,Oncogenes ,medicine.disease ,Prognosis ,Identification (information) ,030104 developmental biology ,Hepatocellular carcinoma ,Biomarker (medicine) ,lcsh:Q ,Artificial intelligence ,Liver cancer ,business ,020602 bioinformatics ,Algorithms - Abstract
Identification of cancer prognostic genes is important in that it can lead to accurate outcome prediction and better therapeutic trials for cancer patients. Many computational approaches have been proposed to achieve this goal; however, there is room for improvement. Recent developments in deep learning techniques can aid in the identification of better prognostic genes and more accurate outcome prediction, but one of the main problems in the adoption of deep learning for this purpose is that data from cancer patients have too many dimensions, while the number of samples is relatively small. In this study, we propose a novel network-based deep learning method to identify prognostic gene signatures via distributed gene representations generated by G2Vec, which is a modified Word2Vec model originally used for natural language processing. We applied the proposed method to five cancer types including liver cancer and showed that G2Vec outperformed extant feature selection methods, especially for small number of samples. Moreover, biomarkers identified by G2Vec was useful to find significant prognostic gene modules associated with hepatocellular carcinoma.
- Published
- 2018