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020 _a9781402051234
_99781402051234
024 7 _a10.1007/1402051239
_2doi
035 _avtls000335049
039 9 _a201509030250
_bVLOAD
_c201404120916
_dVLOAD
_c201404090654
_dVLOAD
_y201402041250
_zstaff
040 _aMX-SnUAN
_bspa
_cMX-SnUAN
_erda
050 4 _aTK7800-8360
100 1 _aChakrabarty, Krishnendu.
_eeditor.
_9308758
245 1 0 _aDesign Automation Methods and Tools for Microfluidics-Based Biochips /
_cedited by Krishnendu Chakrabarty, Jun Zeng.
264 1 _aDordrecht :
_bSpringer Netherlands,
_c2006.
300 _aIx, 403 páginas
_brecurso en línea.
336 _atexto
_btxt
_2rdacontent
337 _acomputadora
_bc
_2rdamedia
338 _arecurso en línea
_bcr
_2rdacarrier
347 _aarchivo de texto
_bPDF
_2rda
500 _aSpringer eBooks
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.
590 _aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700 1 _aZeng, Jun.
_eeditor.
_9308759
710 2 _aSpringerLink (Servicio en línea)
_9299170
776 0 8 _iEdición impresa:
_z9781402051227
856 4 0 _uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/1-4020-5123-9
_zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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999 _c282258
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