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Record Nr. |
UNINA9910464759903321 |
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Titolo |
Microarrays : current technology, innovations and applications / / edited by Zhili He, Department of Microbiology and Plant Biology, Institute for Environmental Genomics, University of Oklahoma, Norman, OK, USA |
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Pubbl/distr/stampa |
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Norfolk, England : , : Caister Academic Press, , [2014] |
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©2014 |
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ISBN |
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Descrizione fisica |
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1 online resource (258 p.) |
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Disciplina |
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Soggetti |
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DNA microarrays |
Electronic books. |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Contents ; Contents ; Contributors; Contributors; Preface; Preface; 1: Microarrays for Microbial Community Analysis at a Glance; Introduction; 1: Microarrays for Microbial Community Analysis at a Glance; Introduction; Microarrays for microbial community analysis at a glance; Microarrays for microbial community analysis at a glance; Key issues for microarray analysis; Key issues for microarray analysis; Applications of microarrays for profiling microbial communities; Applications of microarrays for profiling microbial communities |
Advantages and limitations of microarrays for microbial community analysisAdvantages and limitations of microarrays for microbial community analysis; Conclusions and future directions; Conclusions and future directions; 2: Software Tools for the Selection of Oligonucleotide Probes for Microarrays; Introduction; 2: Software Tools for the Selection of Oligonucleotide Probes for Microarrays; Introduction; General criteria for probe design; General criteria for probe design; Probe design algorithms for microbial DNA microarrays; Probe design algorithms for microbial DNA microarrays |
Discussion/challenges and future trendsDiscussion/challenges and future trends; Conclusions; Online resources for oligonucleotide probe design programs and databases; Conclusions; Online resources for |
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oligonucleotide probe design programs and databases; 3: Development and Evaluation of Functional Gene Arrays with GeoChip as an Example; Introduction; 3: Development and Evaluation of Functional Gene Arrays with GeoChip as an Example; Introduction; FGA development; FGA development; FGA construction and experimental evaluation; FGA construction and experimental evaluation |
Core functional gene families covered by GeoChipsCore functional gene families covered by GeoChips; Challenges and future directions; Challenges and future directions; 4: Microarray Data Analysis; Introduction; Microarray image process; 4: Microarray Data Analysis; Introduction; Microarray image process; Microarray data preprocessing; Microarray data preprocessing; Statistical analysis; Statistical analysis; Conclusions/challenges and future trends; Conclusions/challenges and future trends; 5: Microarray of 16S rRNA Gene Probes for Quantifying Population Differences Across Microbiome Samples |
IntroductionMicroarray of 16S rRNA Gene Probes for Quantifying Population Differences Across Microbiome Samples; Introduction; PhyloChip G3 data analysis; PhyloChip G3 data analysis; Discussion and future trends; Discussion and future trends; Conclusions; Conclusions; 6: GeoChip Applications in Bioremediation Studies; Introduction; Functional gene arrays for bioremediation studies; 6: GeoChip Applications in Bioremediation Studies; Introduction; Functional gene arrays for bioremediation studies; GeoChip design; GeoChip design; Application of GeoChip to bioremediation studies |
Application of GeoChip to bioremediation studies |
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Sommario/riassunto |
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Microorganisms are the most diverse group of organisms and play important and distinctive roles in their ecosystems. They interact with their peers and other organisms (e.g., plants, animals) to form a complicated food web, significantly impacting ecosystem functions and services. However, understanding the diversity, composition, structure, function, activity, and dynamics of microbial communities remains challenging. Over the past decade, microarray-based technologies have been developed to address such challenges. This book is focused on current microarray technologies and their application |
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2. |
Record Nr. |
UNINA9910299826503321 |
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Autore |
Xu Long |
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Titolo |
Visual Quality Assessment by Machine Learning / / by Long Xu, Weisi Lin, C.-C. Jay Kuo |
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Pubbl/distr/stampa |
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Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2015 |
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ISBN |
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Edizione |
[1st ed. 2015.] |
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Descrizione fisica |
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1 online resource (142 p.) |
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Collana |
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SpringerBriefs in Signal Processing, , 2196-4084 |
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Disciplina |
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Soggetti |
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Signal processing |
Computer vision |
Computational intelligence |
Signal, Speech and Image Processing |
Computer Vision |
Computational Intelligence |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references at the end of each chapters. |
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Nota di contenuto |
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Introduction -- Fundamental knowledges of machine learning -- Image features and feature processing -- Feature pooling by learning -- Metrics fusion -- Summary and remarks for future research. |
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Sommario/riassunto |
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The book encompasses the state-of-the-art visual quality assessment (VQA) and learning based visual quality assessment (LB-VQA) by providing a comprehensive overview of the existing relevant methods. It delivers the readers the basic knowledge, systematic overview and new development of VQA. It also encompasses the preliminary knowledge of Machine Learning (ML) to VQA tasks and newly developed ML techniques for the purpose. Hence, firstly, it is particularly helpful to the beginner-readers (including research students) to enter into VQA field in general and LB-VQA one in particular. Secondly, new development in VQA and LB-VQA particularly are detailed in this book, which will give peer researchers and engineers new insights in VQA. |
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