Heterogeneous network embedding enabling accurate disease association predictions

• Published in: BMC medical genomics Vol. 12; no. S10; pp. 186 - 17
• Main Authors: Xiong, Yun, Guo, Mengjie, Ruan, Lu, Kong, Xiangnan, Tang, Chunlei, Zhu, Yangyong, Wang, Wei
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 23.12.2019; BioMed Central; BMC
• Subjects: Analysis; Computational Biology - methods; Datasets; Disease; Disease association prediction; Embedding; Gene mapping; Genes; Genomics; Heterogeneous network; Humans; Machine learning; Medical research; Metabolomics; Metagenomics; MicroRNA; miRNA; Network embedding; Neural networks; Novels; Prostate cancer; Proteins; Proteomics; Semantics; Social networks; Heterogeneous network; Disease association prediction; Network embedding

It is significant to identificate complex biological mechanisms of various diseases in biomedical research. Recently, the growing generation of tremendous amount of data in genomics, epigenomics, metagenomics, proteomics, metabolomics, nutriomics, etc., has resulted in the rise of systematic biologi...