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Design, test, integration and packaging of MEMS/MOEMS, 2005

ANALOG INTEGRATED CIRCUITS AND SIGNAL PROCESSING 2006年第1期48卷 5-5页

作者： Courtois, B Laboratory of Techniques of Informatics and Microelectronics for Computer Architecture (TIMA) CMP Service France ACM ASME IEEE IMAPS IEEE Computer Society Technical University of Budapest Hungary

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Appointments for 2005-2006 term

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IEEE Transactions on Very Large Scale Integration (VLSI) Systems 2005年第7期13卷 773-782页

作者： Ranganathan, Nagarajan Agrawal, Vishwani D. Chakradhar, Srimat T. Chakrabarty, Krishnendu Courtois, Bernard DeMara, Ronald Hu, Xiaobo Sharon Ismail, Yehea I. Jha, Niraj K. John, Lizy Kurian Ker, Ming-Dou Koren, Israel Liu, Bin-Da Marculescu, Diana Marculescu, Radu Narayanan, Vijaykrishnan Nassif, Sani R. Nowick, Steven M. Sapatnekar, Sachin S. Sherlekar, Sunil Sylvester, Dennis Vemuri, Ranga Pham, Michael Department of Computer Science and Engineering University of South Florida Tampa FL 33620 United States Department of Computer Science and Engineering Nanomaterials and Nanomanufacturing Research Center University of South Florida Tampa United States IEEE United States Systems United States Department of Electrical and Computer Engineering Rutgers University New Brunswick NJ United States IETE India ACM NEC Laboratories America Inc. Princeton NJ United States Duke University Durham NC United States ACM SIGDA Sigma Xi United States Laboratory of Techniques of Informatics and Microelectronics for Computer Architectecture ASME IMAPS IEEE Computer Society University of Central Florida Orlando United States Computer Engineering Program SEECS Department of Computer Science and Engineering University of Notre Dame Notre Dame IN United States Northwestern University Evanston IL United States Department of Electrical Engineering Princeton University Princeton NJ United States Association for Computing Machinery Austin United States UT Austin Engineering Foundation United States Department of Electronics Engineering National Chiao-Tung University Taiwan Department of Electrical and Computer Engineering University of Massachusetts Amherst United States Department of Electrical Engineering Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh PA United States Electrical and Computer Engineering Faculty Carnegie Mellon University Pittsburgh PA United States Computer Science and Engineering Department Pennsylvania State University University Park United States IBM Austin Research Laboratory Austin TX United States Columbia University New York NY United States Department of Electrical and Computer Engineering University of Minnesota Minneapolis United States Tata Consultancy Services Centre of Excellence for Embedded Systems India Department of Electrical Engineering IIT Bombay India Department of Electrical Engineering Uni

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SARS-CoV-2 Wastewater Genomic Surveillance: Approaches, Challenges, and Opportunities

arXiv

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arXiv 2023年

作者： Munteanu, Viorel Saldana, Michael Ciorba, Dumitru Bostan, Viorel Su, Justin Maine Kasianchuk, Nadiia Sharma, Nitesh Kumar Knyazev, Sergey Gordeev, Victor Aßmann, Eva Lobiuc, Andrei Covasa, Mihai Crandall, Keith A. Ouyang, Wenhao O. Wu, Nicholas C. Mason, Christopher Tierney, Braden T. Lucaci, Alexander G. Zelikovsky, Alex Mohebbi, Fatemeh Skums, Pavel Gibas, Cynthia Schlueter, Jessica Rzymski, Piotr Solo-Gabriele, Helena Hölzer, Martin Smith, Adam Mangul, Serghei Department of Computers Informatics and Microelectronics Technical University of Moldova Chisinau2045 Moldova Astani Department of Civil and Environmental Engineering University of Southern California 3620 South Vermont Avenue Los AngelesCA90089 United States Titus Family Department of Clinical Pharmacy USC Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences University of Southern California Los AngelesCA90089 United States Laboratory of Molecular Biology Techniques Faculty of Biology Adam Mickiewicz University Poznan61-712 Poland Faculty of Pharmacy Bogomolets National University Kyiv01601 Ukraine Titus Family Department of Clinical Pharmacy USC Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences University of Southern California 1540 Alcazar Street Los AngelesCA90033 United States Department of Pathology and Laboratory Medicine David Geffen School of Medicine University of California Los Angeles Los AngelesCA United States Method Development and Research Infrastructure Robert Koch Institute Berlin13353 Germany Robert Koch Institute Berlin13353 Germany College of Medicine and Biological Sciences University of Suceava Suceava720229 Romania College of Osteopathic Medicine of the Pacific Western University of Health Sciences PomonaCA91766 United States Computational Biology Institute Department of Biostatistics and Bioinformatics Milken Institute School of Public Health George Washington University WashingtonDC20052 United States Department of Biochemistry University of Illinois at Urbana-Champaign UrbanaIL61801 United States Centre for Biophysics and Computational Biology University of Illinois at Urbana-Champaign UrbanaIL61801 United States Carl R. Woese Institute for Genomic Biology University of Illinois at Urbana-Champaign UrbanaIL61801 United States Carle Illinois College of Medicine University of Illinois at Urbana-Champaign UrbanaIL61801 United States Department of Physiology and Biophysics Weill Corne

During the SARS-CoV-2 pandemic, wastewater-based genomic surveillance (WWGS) emerged as an efficient virus surveillance tool capable of accounting for asymptomatic cases, identifying known and novel mutations, and assigning them to lineages and sublineages of the virus. WWGS also offers the potential to uncover novel or cryptic lineages, although identifying and defining these lineages solely from wastewater presents challenges. Besides the significant advantages of WWGS for monitoring SARS-CoV-2 viral spread, technical challenges remain, including coverage dropouts and poor quality of wastewater sequencing (WWS) data due to viral RNA fragmentation and degradation. Subsequently, WWGS analysis requires advanced computational tools that are yet to be developed and benchmarked. The existing bioinformatics tools used to analyze WWS data are often based on previously developed computational methods for variant calling, de-novo assembly, or quantifying the expression of transcripts. Those methods were not specifically developed for WWS data and must be optimized to address unique challenges associated with wastewater analysis. While specialized tools for analyzing WWS data have also been developed recently, it remains to be seen how they will perform given the ongoing evolution of SARS-CoV-2 and the decline in testing and patient-based genomic surveillance. Here, we explore opportunities and challenges associated with WWGS, including aspects such as sample preparation, sequencing technology, and bioinformatics methods. We also highlight its potential role in monitoring infectious diseases and informing public health responses by complementing other surveillance systems. We also critically examine the practical applications and ethical considerations of WWGS, emphasizing the need for a robust framework and its translation into sustainable wastewater surveillance programs to fully realize its potential for public health. © 2023, CC BY.

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