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001 978-1-4020-5123-4
003 DE-He213
005 20161121231112.0
007 cr nn 008mamaa
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020 _a9781402051234
_9978-1-4020-5123-4
024 7 _a10.1007/1-4020-5123-9
_2doi
050 4 _aTK7800-8360
050 4 _aTK7874-7874.9
072 7 _aTJF
_2bicssc
072 7 _aTEC008000
_2bisacsh
072 7 _aTEC008070
_2bisacsh
082 0 4 _a621.381
_223
245 1 0 _aDesign Automation Methods and Tools for Microfluidics-Based Biochips
_h[electronic resource] /
_cedited by Krishnendu Chakrabarty, Jun Zeng.
264 1 _aDordrecht :
_bSpringer Netherlands,
_c2006.
300 _aIX, 403 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aMICROFLUIDICS-BASED BIOCHIPS: TECHNOLOGY ISSUES, IMPLEMENTATION PLATFORMS, AND DESIGN AUTOMATION CHALLENGES -- MODELING AND SIMULATION OF ELECTRIFIED DROPLETS AND ITS APPLICATION TO COMPUTER-AIDED DESIGN OF DIGITAL MICROFLUIDICS -- MODELING, SIMULATION AND OPTIMIZATION OF ELECTROWETTING -- ALGORITHMS IN FASTSTOKES AND ITS APPLICATION TO MICROMACHINED DEVICE SIMULATION -- COMPOSABLE BEHAVIORAL MODELS AND SCHEMATIC-BASED SIMULATION OF ELECTROKINETIC LAB-ON-A-CHIP SYSTEMS -- FFTSVD: A FAST MULTISCALE BOUNDARY ELEMENT METHOD SOLVER SUITABLE FOR BIO-MEMS AND BIOMOLECULE SIMULATION -- MACROMODEL GENERATION FOR BIOMEMS COMPONENTS USING A STABILIZED BALANCED TRUNCATION PLUS TRAJECTORY PIECEWISE LINEAR APPROACH -- SYSTEM-LEVEL SIMULATION OF FLOW INDUCED DISPERSION IN LAB-ON-A-CHIP SYSTEMS -- MICROFLUIDIC INJECTOR MODELS BASED ON ARTIFICIAL NEURAL NETWORKS -- COMPUTER-AIDED OPTIMIZATION OF DNA ARRAY DESIGN AND MANUFACTURING -- SYNTHESIS OF MULTIPLEXED BIOFLUIDIC MICROCHIPS -- MODELING AND CONTROLLING PARALLEL TASKS IN DROPLET-BASED MICROFLUIDIC SYSTEMS -- PERFORMANCE CHARACTERIZATION OF A RECONFIGURABLE PLANAR ARRAY DIGITAL MICROFLUIDIC SYSTEM -- A PATTERN-MINING METHOD FOR HIGH-THROUGHPUT LAB-ON-A-CHIP DATA ANALYSIS.
520 _aMicrofluidics-based biochips, also known as lab-on-a-chip or bio-MEMS, are becoming increasingly popular for DNA analysis, clinical diagnostics, and the detection/manipulation of bio-molecules. As the use of microfluidics-based biochips increases, their complexity is expected to become significant due to the need for multiple and concurrent assays on the chip, as well as more sophisticated control mechanisms for resource management. Time-to-market and fault tolerance are also expected to emerge as design considerations. As a result, current full-custom design techniques will not scale well for larger designs. There is a need to deliver the same level of CAD support to the biochip designer that the semiconductor industry now takes for granted. Design Automation Methods and Tools for Microfluidics-Based Biochips deals with all aspects of design automation for microfluidics-based biochips. Experts have contributed chapters on various aspects of biochip design automation. Topics include device modeling; adaptation of bioassays for on-chip implementations; numerical methods and simulation tools; architectural synthesis, scheduling and binding of assay operations; physical design and module placement; fault modeling and testing; reconfiguration methods.
650 0 _aEngineering.
650 0 _aBiotechnology.
650 0 _aBiophysics.
650 0 _aBiological physics.
650 0 _aFluid mechanics.
650 0 _aElectronics.
650 0 _aMicroelectronics.
650 0 _aElectronic circuits.
650 0 _aBiomedical engineering.
650 1 4 _aEngineering.
650 2 4 _aElectronics and Microelectronics, Instrumentation.
650 2 4 _aBiomedical Engineering.
650 2 4 _aCircuits and Systems.
650 2 4 _aBiotechnology.
650 2 4 _aEngineering Fluid Dynamics.
650 2 4 _aBiophysics and Biological Physics.
700 1 _aChakrabarty, Krishnendu.
_eeditor.
700 1 _aZeng, Jun.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781402051227
856 4 0 _uhttp://dx.doi.org/10.1007/1-4020-5123-9
912 _aZDB-2-ENG
950 _aEngineering (Springer-11647)
999 _c508610
_d508610