000 | 03264nam a22005895i 4500 | ||
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001 | 978-3-319-15606-4 | ||
003 | DE-He213 | ||
005 | 20200420221259.0 | ||
007 | cr nn 008mamaa | ||
008 | 150225s2015 gw | s |||| 0|eng d | ||
020 |
_a9783319156064 _9978-3-319-15606-4 |
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024 | 7 |
_a10.1007/978-3-319-15606-4 _2doi |
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050 | 4 | _aQ295 | |
050 | 4 | _aQA402.3-402.37 | |
072 | 7 |
_aGPFC _2bicssc |
|
072 | 7 |
_aSCI064000 _2bisacsh |
|
072 | 7 |
_aTEC004000 _2bisacsh |
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082 | 0 | 4 |
_a519 _223 |
100 | 1 |
_aAhsen, Mehmet Eren. _eauthor. |
|
245 | 1 | 0 |
_aAnalysis of Deterministic Cyclic Gene Regulatory Network Models with Delays _h[electronic resource] / _cby Mehmet Eren Ahsen, Hitay �Ozbay, Silviu-Iulian Niculescu. |
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Birkh�auser, _c2015. |
|
300 |
_aXIII, 94 p. 15 illus. in color. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
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490 | 1 |
_aSpringerBriefs in Electrical and Computer Engineering, _x2191-8112 |
|
505 | 0 | _aPreface -- Introduction -- Basic Tools from Systems and Control Theory -- Functions with Negative Schwarzian Derivatives -- Deterministic ODE-Based Model with Time Delay -- Gene Regulatory Networks under Negative Feedback -- Gene Regulatory Networks under Positive Feedback -- Summary and Concluding Remarks -- References. | |
520 | _aThis brief examines a deterministic, ODE-based model for gene regulatory networks (GRN) that incorporates nonlinearities and time-delayed feedback. An introductory chapter provides some insights into molecular biology and GRNs. The mathematical tools necessary for studying the GRN model are then reviewed, in particular Hill functions and Schwarzian derivatives. One chapter is devoted to the analysis of GRNs under negative feedback with time delays and a special case of a homogenous GRN is considered. Asymptotic stability analysis of GRNs under positive feedback is then considered in a separate chapter, in which conditions leading to bi-stability are derived. Graduate and advanced undergraduate students and researchers in control engineering, applied mathematics, systems biology and synthetic biology will find this brief to be a clear and concise introduction to the modeling and analysis of GRNs. | ||
650 | 0 | _aMathematics. | |
650 | 0 | _aGene expression. | |
650 | 0 | _aSystem theory. | |
650 | 0 | _aBiomathematics. | |
650 | 0 | _aControl engineering. | |
650 | 0 | _aRobotics. | |
650 | 0 | _aMechatronics. | |
650 | 1 | 4 | _aMathematics. |
650 | 2 | 4 | _aSystems Theory, Control. |
650 | 2 | 4 | _aMathematical and Computational Biology. |
650 | 2 | 4 | _aGene Expression. |
650 | 2 | 4 | _aControl, Robotics, Mechatronics. |
700 | 1 |
_a�Ozbay, Hitay. _eauthor. |
|
700 | 1 |
_aNiculescu, Silviu-Iulian. _eauthor. |
|
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer eBooks | |
776 | 0 | 8 |
_iPrinted edition: _z9783319156057 |
830 | 0 |
_aSpringerBriefs in Electrical and Computer Engineering, _x2191-8112 |
|
856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-3-319-15606-4 |
912 | _aZDB-2-ENG | ||
942 | _cEBK | ||
999 |
_c53098 _d53098 |