ArticleBMC systems biology2014
Computational analysis of the roles of ER-Golgi network in the cell cycle.
Article in BMC systems biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed, 18 citations in OpenAlex.
- Transportome Malfunctions and the Hallmarks of Pancreatic Cancer.Reviews of physiology, biochemistry and pharmacology · 2021Review
- An Integrative Analysis of Time-varying Regulatory Networks From High-dimensional Data.Proceedings : ... IEEE International Conference on Big Data. IEEE International Conference on Big Data · 2018Article
- Predicting Drug Combination Index and Simulating the Network-Regulation Dynamics by Mathematical Modeling of Drug-Targeted EGFR-ERK Signaling Pathway.Scientific reports · 2017Article
- Nuclear Expression of GS28 Protein: A Novel Biomarker that Predicts Prognosis in Colorectal Cancers.International journal of medical sciences · 2017Article
- A Novel Method to Verify Multilevel Computational Models of Biological Systems Using Multiscale Spatio-Temporal Meta Model Checking.PloS one · 2016Article
- A novel procedure for statistical inference and verification of gene regulatory subnetwork.BMC bioinformatics · 2015Article
- InCoB2014: Systems Biology update from the Asia-Pacific. Introduction.BMC systems biology · 2014Article
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Authors and funding
2 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundER-Golgi network plays an important role in the processing, sorting and transport of proteins, and it's also a site for many signaling pathways that regulate the cell cycle. Accumulating evidence suggests that, the stressed ER and malfunction of Golgi apparatus are associated with the pathogenesis of cancer and Alzheimer's disease (AD). Our previous work discovered and verified that altering the expression levels of target SNARE and GEF could modulate the size of Golgi apparatus. Moreover, Golgi's structure and size undergo dramatic changes during the development of several diseases. It is of importance to investigate the roles of ER-Golgi network in the cell cycle progression and some diseases.
resultsIn this work, we first develop a computational model to study the ER stress-induced and Golgi-related apoptosis-survival signaling pathways. Then, we propose and apply both asynchronous and synchronous model checking methods, which extend our previous verification technique, to automatically and formally analyze the ER-Golgi-regulated signaling pathways in the cell cycle progression through verifying some computation tree temporal logic formulas.
conclusionsThe proposed asynchronous and synchronous verification technique has advantages for large network analysis and verification over traditional simulation methods. Using the model checking method, we verified several Alzheimer's disease and cancer-related properties, and also identified important proteins (NFκB, ATF4, ASK1 and TRAF2) in the ER-Golgi network, which might be responsible for the pathogenesis of cancer and AD. Our studies indicate that targeting the ER stress-induced and Golgi-related pathways might serve as potent therapeutic targets for the treatment of cancer and Alzheimer's disease.
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