Knowledge Extraction from Microarray Datasets Using Combined Multiple Models to Predict Leukemia Types

2008 ◽  
pp. 339-352
Author(s):  
Gregor Stiglic ◽  
Nawaz Khan ◽  
Peter Kokol
Keyword(s):  
Knowledge Extraction ◽  
Multiple Models ◽  
Microarray Datasets

A Multi-Language System For Knowledge Extraction In E-Learning Videos

2006 ◽  
Vol 3 (1) ◽  
pp. 48-55
Author(s):  
Aparesh Sood ◽  
◽  
Ankush Mittal ◽  
Divya Sarthi ◽  
◽  
...  
Keyword(s):  
Knowledge Extraction ◽  
Language System ◽  
E Learning

Organising Modern Synagogues: A Case of Multiple Models

2001 ◽  
Vol 34 (2) ◽  
Author(s):  
Margaret Harris
Keyword(s):  
Multiple Models

Multiple Models Direct Adaptive Decoupling Controller for a Stochastic System

2010 ◽  
Vol 36 (9) ◽  
pp. 1295-1304 ◽  
Author(s):  
Yi-Hui ZHENG ◽  
Xin WANG ◽  
Shao-Yuan LI ◽  
Jian-Guo JIANG
Keyword(s):  
Stochastic System ◽  
Multiple Models

Cloud Provider's Response to Multiple Models of Attack Behaviors

2019 ◽  
Vol 13 (4) ◽  
pp. 325-333
Author(s):  
Xu Liu ◽  
Xiaoqiang Di ◽  
Jinqing Li ◽  
Huamin Yang ◽  
Ligang Cong ◽  
...  
Keyword(s):  
Stackelberg Game ◽  
Multiple Models ◽  
Theoretic Model ◽  
Cloud Provider ◽  
Game Model ◽  
Attack Behavior ◽  
Behavior Model ◽  
Protection Strategy ◽  
Behavior Models ◽  
Optimal Protection

Background: User behavior models have been widely used to simulate attack behaviors in the security domain. We revised all patents related to response to attack behavior models. How to decide the protected target against multiple models of attack behaviors is studied. Methods: We utilize one perfect rational and three bounded rational behavior models to simulate attack behaviors in cloud computing, and then investigate cloud provider’s response based on Stackelberg game. The cloud provider plays the role of defender and it is assumed to be intelligent enough to predict the attack behavior model. Based on the prediction accuracy, two schemes are built in two situations. Results: If the defender can predict the attack behavior model accurately, a single-objective game model is built to find the optimal protection strategy; otherwise, a multi-objective game model is built to find the optimal protection strategy. Conclusion: The numerical results prove that the game theoretic model performs better in the corresponding situation.

Mechanisms, Models, and Kinds

2017 ◽  
Author(s):  
Stuart Glennan
Keyword(s):  
Natural Kinds ◽  
Multiple Models

This chapter explores how mechanisms and their constituents can be classified into kinds. It argues for a weakly realist account of natural kinds—one which suggests that classification into kinds is based upon real similarities between instances of those kinds, but which denies that kinds have essences or have some reality apart from their instances. I introduce a models-first account of kinds, which suggests that two things are of the same kind to the extent that they can be represented by the same model. Because target entities can be represented by multiple models, they will belong to multiple kinds. I illustrate the approach by showing how the entities and activities that make up mechanisms can be classified into kinds.

Population Viability of Rorippa columbiae: Multiple Models and Spatial Trend Data

1998 ◽  
Vol 12 (5) ◽  
pp. 1054-1065 ◽  
Author(s):  
Elizabeth E. Crone ◽  
Janet L. Gehring
Keyword(s):  
Population Viability ◽  
Multiple Models ◽  
Spatial Trend ◽  
Trend Data ◽  
Rorippa Columbiae

scholarly journals Rewired Pathways and Disrupted Pathway Crosstalk in Schizophrenia Transcriptomes by Multiple Differential Coexpression Methods

Genes ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 665
Author(s):  
Hui Yu ◽  
Yan Guo ◽  
Jingchun Chen ◽  
Xiangning Chen ◽  
Peilin Jia ◽  
...  
Keyword(s):  
Gene Expression ◽  
Focal Adhesion ◽  
Biological Pathways ◽  
Postmortem Brain ◽  
Rna Seq ◽  
Hub Genes ◽  
Differential Coexpression ◽  
Pathway Crosstalk ◽  
Microarray Datasets ◽  
Transcriptomic Studies

Transcriptomic studies of mental disorders using the human brain tissues have been limited, and gene expression signatures in schizophrenia (SCZ) remain elusive. In this study, we applied three differential co-expression methods to analyze five transcriptomic datasets (three RNA-Seq and two microarray datasets) derived from SCZ and matched normal postmortem brain samples. We aimed to uncover biological pathways where internal correlation structure was rewired or inter-coordination was disrupted in SCZ. In total, we identified 60 rewired pathways, many of which were related to neurotransmitter, synapse, immune, and cell adhesion. We found the hub genes, which were on the center of rewired pathways, were highly mutually consistent among the five datasets. The combinatory list of 92 hub genes was generally multi-functional, suggesting their complex and dynamic roles in SCZ pathophysiology. In our constructed pathway crosstalk network, we found “Clostridium neurotoxicity” and “signaling events mediated by focal adhesion kinase” had the highest interactions. We further identified disconnected gene links underlying the disrupted pathway crosstalk. Among them, four gene pairs (PAK1:SYT1, PAK1:RFC5, DCTN1:STX1A, and GRIA1:MAP2K4) were normally correlated in universal contexts. In summary, we systematically identified rewired pathways, disrupted pathway crosstalk circuits, and critical genes and gene links in schizophrenia transcriptomes.

Sign in / Sign up

Export Citation Format

Share Document