Uncovering Gene Regulatory Networks from DNA-microarray Data for Escherichia coli by Using A Neural Network Approach

سال انتشار: 1384
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 2,071

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شناسه ملی سند علمی:

ICIKT02_096

تاریخ نمایه سازی: 12 دی 1386

چکیده مقاله:

Cells regulate their gene expression patterns in response to changes in environmental and physiological conditions This process of transcriptional regulation is carried out through a complex network of highly-interacted regulatory components whose properly inference necessitates employment of computational methodologies based on a global, genome-wide scale using ideas from system identification. Using a neural network approach, we demonstrated that this complex network of co-regulated genes can be described by only a few number of transcriptional regulators. We also examined the capability of this neural network approach in determining dynamics of multiple transcription factor activities, which can be considered as regulatory signals, using only DNA microarray data. We applied this approach to the regulatory network of Escherichia coli bacterium during carbon source transition from glucose to acetate. Key results from this analysis were either consistent with physiology or verified by using independent measurements..

نویسندگان

Alireza Zomorrodi

Master’s student of Biochemical Engineering، Department of Chemical Engineering, AmirKabir University of Technology (Tehran Polytechnic), Tehran, Iran.

Bahram Nasernejad

Associate Prof. of Chemical Engineering، Department of Chemical Engineering, AmirKabir University of Technology (Tehran Polytechnic), Tehran, Iran.

Jahanshah Kabudian

Department of Computer Engineering & Information Technology, AmirKabir University of Technology (Tehran Polytechnic), Tehran, Iran.

Majid Raissi Dehkordi

Department of Computer Engineering & Information Technology, AmirKabir University of Technology (Tehran Polytechnic), Tehran, Iran.

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  • N. S. Holter, M. Mitra, A. Maritan, M. Cieplak, J. ...
  • modeling of gene Dynamic؛ [6] N. S. Holter, A. Maritan, ...
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  • A. J. Cozzone, *Regulation of acetate metabolism by protein ph ...
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  • J. A. Quan, B. L Schneider., I. T. Paulsen, M. ...
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