연구자료실2019-01-07T08:08:11+00:00

 

TitleWhat We Learned From Big Data for Autophagy Research2018-12-20 05:34:42
CategoryResearch
Writer Level 10

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.

Keywords: autophagy, big data, proteomics, bioinformatics, transcriptomics

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출처: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6107789/