Reliability analysis for complex system with multi-source data integration and multi-level data transmission

2021 ◽  
pp. 108050
Author(s):  
Xiang Jia ◽  
Bo Guo
Keyword(s):  
Complex System ◽  
Data Integration ◽  
Reliability Analysis ◽  
Data Transmission ◽  
Level Data ◽  
Source Data ◽  
Multi Level

scholarly journals Reliability analysis of a complex system with hybrid structures and multi-level dependent life metrics

2021 ◽  
Vol 209 ◽  
pp. 107469
Author(s):  
Lechang Yang ◽  
Pidong Wang ◽  
Qiang Wang ◽  
Sifeng Bi ◽  
Rui Peng ◽  
...  
Keyword(s):  
Complex System ◽  
Reliability Analysis ◽  
Hybrid Structures ◽  
Multi Level

Dissecting metabolic behavior of lipid over-producing strain of Mucor circinelloides through genome-scale metabolic network and multi-level data integration

Gene ◽  
2018 ◽  
Vol 670 ◽  
pp. 87-97 ◽  
Author(s):  
Wanwipa Vongsangnak ◽  
Amornthep Kingkaw ◽  
Junhuan Yang ◽  
Yuanda Song ◽  
Kobkul Laoteng
Keyword(s):  
Data Integration ◽  
Metabolic Network ◽  
Mucor Circinelloides ◽  
Level Data ◽  
Multi Level ◽  
Metabolic Behavior ◽  
Genome Scale

Multi-level approach for important component identification and reliability evaluation for complex system by survival signature

2019 ◽  
Vol 37 (1) ◽  
pp. 262-288
Author(s):  
Liling Ge ◽  
Yingjie Zhang
Keyword(s):  
Complex System ◽  
Complex Systems ◽  
Reliability Analysis ◽  
Production System ◽  
Content Type ◽  
Actual Production ◽  
Machining System ◽  
Multi Level ◽  
Critical Components

Purpose The purpose of this paper is to identify the critical components of a complex system by using survival signature. First, a complex system is abstracted with varying scales and generates a multi-levels model. Then reliability evaluations can be conducted by survival signature from rough to fine for tracing and identifying them. Finally, the feasibility of the proposed approach is demonstrated by an actual production system. Design/methodology/approach The paper mainly applies a multi-level evaluating strategy for the reliability analysis of complex systems with components of multiple types. In addition, a multi-levels model of a complex system is constructed and survival signature also used for evaluation. Findings The proposed approach was demonstrated to be the feasibility by an actual production system that is used in the case study. Research limitations/implications The case study was performed on a system with simple network structure, but the proposed approach could be applied to systems with complex ones. However, the approach to generate the digraphs of abstraction levels for complex system has to be developed. Practical implications So far the approach has been used for the reliability analysis of a machining system. The approach that is proposed for the identification of critical components also can be applied to make maintenance decision. Originality/value The multi-level evaluating strategy that was proposed for reliability analysis and the identification of critical components of complex systems was a novel method, and it also can be applied as index to make maintenance planning.

scholarly journals Evaluating the Pharmacological Mechanism of Chinese Medicine Si-Wu-Tang through Multi-Level Data Integration

PLoS ONE ◽  
2013 ◽  
Vol 8 (11) ◽  
pp. e72334 ◽  
Author(s):  
Zhao Fang ◽  
Bingxin Lu ◽  
Mingyao Liu ◽  
Meixia Zhang ◽  
Zhenghui Yi ◽  
...  
Keyword(s):  
Chinese Medicine ◽  
Data Integration ◽  
Pharmacological Mechanism ◽  
Level Data ◽  
Multi Level

Multi-Level Data Integration and Data Mining in Systems Biology

2009 ◽  
pp. 476-496 ◽  
Author(s):  
Roberta Alfieri ◽  
Luciano Milanesi
Keyword(s):  
Data Mining ◽  
Cell Cycle ◽  
Systems Biology ◽  
Data Integration ◽  
Data Mining Techniques ◽  
Level Data ◽  
Pathway Data ◽  
Multi Level ◽  
First Time ◽  
Cell Cycle Models

This chapter aims to describe data integration and data mining techniques in the context of systems biology studies. It argues that the different methods available in the field of data integration can be very useful in making research in the field of systems biology easier. Moreover data mining is an important task to take into account in this context, therefore in this chapter, some aspects of data mining applied to systems biology specific case studies shall be discussed. The availability of a large number of specific resources, especially for the experimental researchers, is something difficult for users who tried to explore gene, protein, and pathway data for the first time. This chapter finally aims to highlight the complexity in the systems biology data and to provide an overview of the data integration and mining approaches in the context of systems biology using a specific example for the Cell Cycle database and the Cell Cycle models simulation.

miRNA-mediated Drug Repurposing Unveiled Potential Candidate Drugs for Prolactinoma Treatment

2021 ◽  
Author(s):  
Büşra Aydin ◽  
Sema Arslan ◽  
Fatih Bayraklı ◽  
Betül Karademir ◽  
Kazim Yalcin Arga
Keyword(s):  
Cell Cycle ◽  
Data Integration ◽  
Cell Viability ◽  
Drug Repurposing ◽  
Serum Prolactin ◽  
Drug Candidates ◽  
Mirna Level ◽  
Level Data ◽  
Cell Cycle Phases

Introduction: Prolactinomas, also called lactotroph adenomas, are the most encountered type of hormone-secreting pituitary neuroendocrine tumors (PitNET) in the clinic. The preferred first-line therapy is a medical treatment with dopamine agonists (DA), mainly cabergoline, to reduce serum prolactin levels, tumor volume, and mass effect. However, in some cases, patients have displayed DA-resistance with aggressive tumor behavior or are faced with recurrence after drug withdrawal. Also, currently used therapeutics have notorious side effects and impair the life quality of the patients. Methods: Since the amalgamation of clinical and laboratory data besides tumor histopathogenesis and transcriptional regulatory features of the tumor emerge to exhibit essential roles in the behavior and progression of prolactinomas, in this work, we integrated mRNA and microRNA (miRNA) level transcriptome data that exploit disease-specific signatures in addition to biological and pharmacological data to elucidate a rational prioritization of pathways and drugs in prolactinoma. Results: We identified eight drug candidates through drug repurposing based on mRNA-miRNA level data integration and evaluated their potential through in vitro assays in the MMQ cell line. Seven re-purposed drugs including 5-flourocytosine, nortriptyline, neratinib, puromycin, taxifolin, vorinostat, and zileuton were proposed as potential drug candidates for the treatment of prolactinoma. We further hypothesized possible mechanisms of drug action on MMQ cell viability through analyzing PI3K/Akt signaling pathway and cell cycle arrest via flow cytometry and western blotting. Discussion: We presented the transcriptomic landscape of prolactinoma through miRNA and mRNA level data integration and proposed repurposed drug candidates based on this integration. We validated our findings through testing cell viability, cell cycle phases, and PI3K/Akt protein expressions. Effects of the drugs on cell cycle phases and inhibition of PI3K/Akt pathway by all drugs gave us promising output for further studies using these drugs in the treatment of prolactinoma. This is the first study that reports miRNA-mediated repurposed drugs for prolactinoma treatment via in vitro experiments.

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