Frontiers in Cell and Developmental Biology | |
What We Learned From Big Data for Autophagy Research | |
Lejla Gul1  Padhmanand Sudhakar2  Tamas Korcsmaros2  Ioannis P. Nezis3  Anne-Claire Jacomin3  | |
[1] Earlham Institute, Norwich Research Park, Norwich, United Kingdom;Gut Microbes and Health Programme, Quadram Institute, Norwich Research Park, Norwich, United Kingdom;School of Life Sciences, University of Warwick, Coventry, United Kingdom; | |
关键词: autophagy; big data; proteomics; bioinformatics; transcriptomics; | |
DOI : 10.3389/fcell.2018.00092 | |
来源: DOAJ |
【 摘 要 】
Autophagy is the process by which cytoplasmic components are engulfed in double-membraned vesicles before being delivered to the lysosome to be degraded. Defective autophagy has been linked to a vast array of human pathologies. The molecular mechanism of the autophagic machinery is well-described and has been extensively investigated. However, understanding the global organization of the autophagy system and its integration with other cellular processes remains a challenge. To this end, various bioinformatics and network biology approaches have been developed by researchers in the last few years. Recently, large-scale multi-omics approaches (like genomics, transcriptomics, proteomics, lipidomics, and metabolomics) have been developed and carried out specifically focusing on autophagy, and generating multi-scale data on the related components. In this review, we outline recent applications of in silico investigations and big data analyses of the autophagy process in various biological systems.
【 授权许可】
Unknown