自噬
粒体自噬
计算生物学
生物
资源(消歧)
数据集成
计算机科学
转录组
元数据
细胞生物学
生物信息学
数据库
万维网
遗传学
基因
细胞凋亡
计算机网络
基因表达
作者
Luca Csabai,Balazs Bohar,Dénes Türei,Sowmya R Prabhu,László Földvári-Nagy,Matthew Madgwick,Dávid Fazekas,Dezso Modos,Marton Olbei,Themis Halka,Martina Poletti,P Kornilova,Tamás Kadlecsik,Attila Demeter,Mate Szalay-Beko,Orsolya Kapuy,Katalin Lenti,Tibor Vellai,Lejla Gul,Tamas Korcsmaros
标识
DOI:10.1101/2023.03.30.534858
摘要
Abstract Autophagy is a highly-conserved catabolic process eliminating dysfunctional cellular components and invading pathogens. Autophagy malfunction contributes to disorders such as cancer, neurodegenerative and inflammatory diseases. Understanding autophagy regulation in health and disease has been the focus of the last decades. We previously provided an integrated database for autophagy research, the Autophagy Regulatory Network (ARN). For the last seven years, this resource has been used by thousands of users. Here, we present a new and upgraded resource, AutophagyNet. It builds on the previous database but contains major improvements to address user feedback and novel needs due to the advancement in omics data availability. AutophagyNet contains updated interaction curation and integration of over 280,000 experimentally verified interactions between core autophagy proteins and their protein, transcriptional and post-transcriptional regulators as well as their potential upstream pathway connections. AutophagyNet provides annotations for each core protein about their role: 1) in different types of autophagy (mitophagy, xenophagy, etc.); 2) in distinct stages of autophagy (initiation, elongation, termination, etc); 3) with subcellular and tissue-specific localization. These annotations can be used to filter the dataset, providing customizable download options tailored to the user’s needs. The resource is available in various file formats (e.g., CSV, BioPAX and PSI-MI), and data can be analyzed and visualized directly in Cytoscape. The multi-layered regulation of autophagy can be analyzed by combining AutophagyNet with tissue- or cell type-specific using (multi-)omics datasets (e.g. transcriptomic or proteomic data). The resource is publicly accessible at http://autophagynet.org .
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