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Learning Technology for Education Challenges
This book constitutes the refereed proceedings of the 6th International Workshop on Learning Technology for Education in Cloud, LTEC 2017, held in Beijing, China, in August 2017. The 16 revised full papers presented were carefully reviewed and selected from 37 submissions. The papers are organized in topical sections on Learning Technologies; Learning Tools and Environment; Online Learning and MOOC; Problem Solving and Knowledge Transfer.
Genome-Scale Algorithm Design
Guided by standard bioscience workflows in high-throughput sequencing analysis, this book for graduate students, researchers, and professionals in bioinformatics and computer science offers a unified presentation of genome-scale algorithms. This new edition covers the use of minimizers and other advanced data structures in pangenomics approaches.
Clustering Stability
A popular method for selecting the number of clusters is based on stability arguments: one chooses the number of clusters such that the corresponding clustering results are most stable. In recent years, a series of papers has analyzed the behavior of this method from a theoretical point of view. However, the results are very technical and difficult to interpret for non-experts. In this paper we give a high-level overview about the existing literature on clustering stability. In addition to presenting the results in a slightly informal but accessible way, we relate them to each other and discuss their different implications.
Experimental Algorithms
This volume constitutes the refereed proceedings of the 10th International Symposium on Experimental Algorithms, SEA 2011, held in Kolimpari, Chania, Crete, Greece, in May 2011. The 36 revised full papers presented together with 2 invited papers were carefully reviewed and selected from 83 submissions and present current research in the area of design, analysis, and experimental evaluation and engineering of algorithms, as well as in various aspects of computational optimization and its applications.
Current Topics in Computational Molecular Biology
A survey of current topics in computational molecular biology. Computational molecular biology, or bioinformatics, draws on the disciplines of biology, mathematics, statistics, physics, chemistry, computer science, and engineering. It provides the computational support for functional genomics, which links the behavior of cells, organisms, and populations to the information encoded in the genomes, as well as for structural genomics. At the heart of all large-scale and high-throughput biotechnologies, it has a growing impact on health and medicine. This survey of computational molecular biology covers traditional topics such as protein structure modeling and sequence alignment, and more recent ones such as expression data analysis and comparative genomics. It combines algorithmic, statistical, database, and AI-based methods for studying biological problems. The book also contains an introductory chapter, as well as one on general statistical modeling and computational techniques in molecular biology. Each chapter presents a self-contained review of a specific subject. Not for sale in China, including Hong Kong.
Vector Quantization and Signal Compression
Herb Caen, a popular columnist for the San Francisco Chronicle, recently quoted a Voice of America press release as saying that it was reorganizing in order to "eliminate duplication and redundancy. " This quote both states a goal of data compression and illustrates its common need: the removal of duplication (or redundancy) can provide a more efficient representation of data and the quoted phrase is itself a candidate for such surgery. Not only can the number of words in the quote be reduced without losing informa tion, but the statement would actually be enhanced by such compression since it will no longer exemplify the wrong that the policy is supposed to correct. Here compression can str...
An Introduction to Bioinformatics
Bioinformatics is an amalgamation of mathematics, engineering, computer sciences and statistics. It refers to the practice of using software tools to understand biological data. This book explores all the important aspects of bioinformatics in the present day scenario. It elaborates the different branches related to the subject and their applications. While understanding the long-term perspectives of the topics, the book makes an effort in highlighting their impact as a modern tool for the growth of bioinformatics. This text, with its detailed analyses and data, will prove immensely beneficial to students involved in this area at various levels. It will be of great help to those in the fields of genetics, forensic science and evolutionary biology.
