Title Algorithms for Sample Preparation with Microfluidic Lab-on-Chip
Subtitle
Author Sukanta Bhattacharjee, Bhargab B. Bhattacharya, Krishnendu Chakrabarty
ISBN 9788770220552
List price USD 107.00
Price outside India Available on Request
Original price
Binding Hardbound
No of pages 250
Book size 153 x 235 mm
Publishing year 2019
Original publisher River Publishers (Eurospan Group)
Published in India by .
Exclusive distributors Viva Books Private Limited
Sales territory India, Sri Lanka, Bangladesh, Pakistan, Nepal, .
Status New Arrival
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Description:

Recent microfluidic technologies have brought a complete paradigm shift in automating biochemical processing on a tiny lab-on-chip (a.k.a. biochip) that replaces expensive and bulky instruments traditionally used in implementing bench-top laboratory protocols. Biochips have already made a profound impact on various application domains such as clinical diagnostics, DNA analysis, genetic engineering, and drug discovery, among others. They are capable of precisely manipulating micro-/pico-liter quantities of fluids, and provide integrated support for mixing, storage, transportation, and sensing, on-chip. In almost all bioprotocols, sample preparation plays an important role, which includes dilution and mixing of several fluids satisfying certain volumetric ratios. However, designing algorithms that minimize reactant-cost and sample-preparation time suited for microfluidic chips poses a great challenge from the perspective of protocol mapping, scheduling, and physical design.

Algorithms for Sample Preparation with Microfluidic Lab-on-Chip attempts to bridge the widening gap between biologists and engineers by introducing, from the fundamentals, several state-of-the-art computer-aided-design (CAD) algorithms for sample preparation with digital and flow-based microfluidic biochips.

Technical topics discussed in the book include:

  • Basics of digital and flow-based microfluidic lab-on-chip
  • Comprehensive review of state-of-the-art sample preparation algorithms
  • Sample-preparation algorithms for digital microfluidic lab-on-chip
  • Sample-preparation algorithms for flow-based microfluidic lab-on-chip


Contents:

Preface

List of Figures

List of Tables

List of Abbreviations

Chapter 1: Introduction • Basics of Microfluidic Biochips • Design Automation of Microfluidic Biochips • Sample Preparation with Microfluidic Biochips • Organization of the Book

Chapter 2: Sample Preparation with Microfluidic Biochips: A Review • Dilution Algorithms for DMFB • Single-target Dilution Algorithms • Multiple-target Dilution Algorithms • Generation of Dilution Gradients • Mixing Algorithms for DMFB • Droplet Streaming Algorithms • Dilution and Mixing Algorithms for CFMB • Summary

Chapter 3: Multiple Dilution Sample Preparation on Digital Microfluidic Biochips • Related Work • Tree-pruning-based Dilution Algorithm • Proposed Methodology • Experimental Results • Conclusions

Chapter 4: Efficient Generation of Dilution Gradients with Digital Microfluidic Biochips • Literature Review • Linear Gradient • Exponential Gradient • Complex-shaped Gradients • Digital Curve Representation of a Gradient Profile • Identification of DSS on a Gradient Profile • Experimental Results • Linear Gradient • Exponential Gradients • Parabolic, Sinusoidal, and Gaussian Gradients • Conclusions

Chapter 5: Concentration-Resilient Mixture Preparation • Related Work • Motivation and Problem Definition • Proposed Method • An ILP Formulation for Optimal Solution • Experimental Results • Conclusions

Chapter 6: Dilution and Mixing Algorithms for Flow-based Microfluidic Biochips • Sample Preparation and Mixing Models • Related Work • Motivation and Contribution • Overview of the Proposed Method • Dilution • Approximation of the Target Concentration Factor  • Modeling of Dilution • Dilution Algorithm • Mixture Preparation • Approximation of the Target Mixture-Ratio • Generalized Mixing Algorithm • SMT-based Modeling of Reagent-saving Mixing  • Reagent-Saving Mixing Algorithm • Experimental Results • Performance Evaluation for Dilution • Performance Evaluation for Reagent-Saving Mixing • Performance of FIoSPA on Real-life Dilution and Mixing Ratios • Conclusions

Chapter 7: Storage-Aware Algorithms for Dilution and Mixture Preparation with Flow-Based Lab-on-Chip • Related Works • Storage-Aware Sample Preparation • Overview • Storage-Aware Dilution • Overview of the Storage-Aware Mixing • Experimental Results • Performance for Dilution • Performance for Mixing • Conclusions

Chapter 8: Conclusion and Future Directions

Bibliography

Index

About the Authors


About the Authors:

Sukanta Bhattacharjee received the B.Tech. degree in computer science and engineering from the University of Calcutta, India and the M.Tech. and Ph.D. degrees in computer science from the Indian Statistical Institute, Kolkata, India. He is currently working as a post-doctoral associate in the Center for Cyber Security, New York University, Abu Dhabi.

His research interests include design automation algorithms for microfluidic biochip, formal methods, and security.

Bhargab B. Bhattacharya had been on the standing faculty of Computer Science and Engineering at the Indian Statistical Institute, Kolkata, during 1982-2018, where currently, he is associated as Honorary Visiting Professor after his retirement. He received the B.Sc. degree in physics, the B.Tech. and M.Tech. degrees in radiophysics and electronics, and the Ph.D. degree in computer science, all from the University of Calcutta.

He held visiting professorship at the University of Nebraska-Lincoln, and at Duke University, USA, at the University of Potsdam, Germany, at the Kyushu Institute of  Technology, Japan, at Tsinghua University, Beijing, China, at IIT Kharagpur and IIT Guwahati, India. His current research interest includes design and test of integrated circuits and microfluidic biochips. He is a Fellow of the Indian National Academy of Engineering (INAE), a Fellow of the National Academy of Sciences (India), and a Fellow of the IEEE. He was named INAE Chair Professor (2016-18), and AICTE-INAE Distinguished Visiting Professor (2018-20).

Krishnendu Chakrabarty received the B.Tech. degree from the Indian Institute of Technology, Kharagpur, in 1990, and the M.S.E. and Ph.D. degrees from the University of Michigan, Ann Arbor, in 1992 and 1995, respectively. He is now the William H. Younger Distinguished Professor and Department Chair of Electrical and Computer Engineering and Professor of Computer Science at Duke University.

Prof. Chakrabarty is a recipient of the National Science Foundation CAREER award, the Office of Naval Research Young Investigator award, the Humboldt Research Award from the Alexander von Humboldt Foundation, Germany, the IEEE Transactions on CAD Donald O. Pederson Best Paper Award the ACM Transactions on Design Automation of Electronic Systems Best Paper Award and over a dozen best paper awards at major conferences. He is also a recipient of the IEEE Computer Society Technical Achievement Award the IEEE Circuits and Systems Society Charles A. Desoer Technical Achievement Award and the Distinguished Alumnus Award from the Indian Institute of Technology, Kharagpur. He is a Research Ambassador of the University of Bremen, Germany, and a Hans Fischer Senior Fellow at the Institute for Advanced Study, Technical University of Munich, Germany. He is also a recipient of the Japan Society for the Promotion of Science (JSPS) Prestigious Fellowship in the Short-Term S-Category. Prof. Chakrabartys current research interests include: testing and design-for-testability of integrated circuits and systems; digital microfluidics, biochips, and cyberphysical systems; data analytics for fault diagnosis, failure prediction, anomaly detection, and hardware security; neuromorphic computing systems. He is a Fellow of ACM and a Golden Core Member of the IEEE Computer Society.


Target Audience:

This book attempts to bridge the widening gap between biologists and engineers by introducing, from the fundamentals, several state-of-the-art computer-aided-design (CAD) algorithms for sample preparation with digital and flow-based microfluidic biochips.

 

 
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