What We Learned From Big Data for Autophagy Research

Frontiers in Cell and Developmental Biology

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