AUTHOR=Jacomin Anne-Claire , Gul Lejla , Sudhakar Padhmanand , Korcsmaros Tamas , Nezis Ioannis P. TITLE=What We Learned From Big Data for Autophagy Research JOURNAL=Frontiers in Cell and Developmental Biology VOLUME=6 YEAR=2018 URL=https://www.frontiersin.org/journals/cell-and-developmental-biology/articles/10.3389/fcell.2018.00092 DOI=10.3389/fcell.2018.00092 ISSN=2296-634X ABSTRACT=

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.