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Emerging Principles of Gene Expression Programs and Their Regulation [PDF]

Molecular Cell, 2018
Many mechanisms contribute to regulation of gene expression to ensure coordinated cellular behaviors and fate decisions. Transcriptional responses to external signals can consist of many hundreds of genes that can be parsed into different categories based on kinetics of induction, cell-type and signal specificity, and duration of the response.
Scott D, Pope, Ruslan, Medzhitov
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Generate Digital Elevation Model by Gene Expression Programming

工程科学与技术, 2010
: Digital Elevation Model is the foundation to analyze terrain in Geographic Information System. When processing the lost sampled points, the traditional spatial interpolation methods are ineffective and impersonal in selection the interpolation ...
Jiang Yue, Tang Changjie, JIANG Xianfei
doaj  

Mouse embryonic stem cells can differentiate via multiple paths to the same state

eLife, 2017
In embryonic development, cells differentiate through stereotypical sequences of intermediate states to generate particular mature fates. By contrast, driving differentiation by ectopically expressing terminal transcription factors (direct programming ...
James Alexander Briggs, Victor C Li, Seungkyu Lee, Clifford J Woolf, Allon Klein, Marc W Kirschner   +5 more
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Gene Expression Programming With Structured Reusability

International Journal of Cognitive Informatics and Natural Intelligence
In the field of evolutionary computation, gene expression programming (GEP) has been favored by the public because of its straightforward encoding method. Due to the coding rules for the head and tail on gene, the ability of gene to be constructed as an expression is limited, thereby limiting the expressiveness of individuals.
Yaping Zheng, Pei He, Chi-Chang Chang, Kangshun Li   +3 more
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Evaluation of Experimental Models and Artificial Intelligence in Estimation of Reference Evapotranspiration (Case Study: Boroujerd Station)

علوم آب و خاک, 2021
The FAO Penman-Monteith is a baseline method to estimate reference evapotranspiration. In many cases, it is difficult to access all data, so replacing simpler models with ‎lower input data and appropriate accuracy is necessary.
Y. Sabzevari, M. Saeidinia
doaj  

Taiwan Stock Investment with Gene Expression Programming

Procedia Computer Science, 2014
AbstractIn this paper, we first find out some good trading strategies from the historical series and apply them in the future. The profitable strategies are trained out by the gene expression programming (GEP), which involves some well-known stock technical indicators as features.
Cheng-Han Lee, Chang-Biau Yang, Hung-Hsin Chen   +2 more
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Function Optimization Based on Embedded Gene Expression Programming

工程科学与技术, 2010
:The Gene Expression Programming(GEP) usually exists some un-expressed introns,the performance may be lower than GA in simple function optimization and the speed is un-satisfied to complicated optimization task.
Xiang Yong, Tang Changjie, Zeng Tao, Zhang Min   +3 more
doaj  

Genetic Expression Programming Based Empirical Models for the Prediction of Rutting Parameter of Bitumen Modified Using Nanomaterials

Engineered Science
Bitumen rheological properties significantly influence pavement performance in terms of resistance to rutting and cracking. Various approaches, such as polymer modification and the incorporation of nanomaterials, have been employed to improve bitumen ...
Sandra Matarneh, Nawal Louzi, Ibrahim Asi, Mu'tasim Abdel-Jaber, Eyad Masad   +4 more
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A hybrid gene expression programming algorithm based on orthogonal design

International Journal of Computational Intelligence Systems, 2016
The last decade has witnessed a great interest on the application of evolutionary algorithms, such as genetic algorithm (GA), particle swarm optimization (PSO) and gene expression programming (GEP), for optimization problems. This paper presents a hybrid
Jie Yang, Jun Ma
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Multi-Objective Gene Expression Programming for Clustering

Information Technology And Control, 2012
This paper proposes a multi-objective gene expression programming for clustering (MGEPC), which could automatically determine the number of clusters and the appropriate partitioning from the data set. The clustering algebraic operations of gene expression programming are extended first.
Yifei Zheng, Lixin Jia, Hui Cao 0003
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