الصفحة 19
الصفحة 19
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Comparative genomics ; RECOMB 2007, International Workshop, RECOMB-CG 2007, San Diego, CA, USA, September 16-18, 2007, Proceedings

This book provides an evolutionary conceptual framework for comparative genomics, with the ultimate objective of understanding the loss and gain of genes during evolution, the interactions among gene products, and the relationship between genotype, phenotype and the environment. The many examples in the book have been carefully chosen from primary research literature based on two criteria: their biological insight and their pedagogical merit. The phylogeny-based comparative methods, involving both continuous and discrete variables, often represent a stumbling block for many students entering the field of comparative genomics. They are numerically illustrated and explained in great detail.

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Comparative genomics ; International Workshop, RECOMB-CG 2008, Paris, France, October 13-15, 2008. Proceedings

This book constitutes the refereed proceedings of the 6th RECOMB Comparative Genomics Satellite Workshop, RECOMB-CG 2008, held in Paris, France, in October 2008.

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Communications and Discoveries from Multidisciplinary Data

In this book, we aim at urging the development of data-based methods and methodologies for interdisciplinary and creative communications for solving emerging social problems. The reader shall view the direction to combine three methodological frameworks: data mining, data sharing, and communication in the contexts of sciences and businesses.

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Clinical decision support systems : Theory and practice

Writes the editor, "If used properly, CDSS have the potential to change the way medicine has been taught and practiced." As clinical decision support systems (CDSS) gain an increasingly central role in the delivery of high quality health care, it becomes more important for the health care community to understand their use. This text is designed as a resource for practicing clinicians, informaticians, teachers and students alike, and provides the most current, comprehensive look a the development and evaluation of clinical decision support systems.

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Classification and Modeling with Linguistic Information Granules : Advanced Approaches to Linguistic Data Mining

Many approaches have already been proposed for classification and modeling in the literature. These approaches are usually based on mathematical mod­ els. Computer systems can easily handle mathematical models even when they are complicated and nonlinear (e.g., neural networks). On the other hand, it is not always easy for human users to intuitively understand mathe­ matical models even when they are simple and linear. This is because human information processing is based mainly on linguistic knowledge while com­ puter systems are designed to handle symbolic and numerical information. A large part of our daily communication is based on words. We learn from various media such as books, newspapers, magazines, TV, and the Inter­ net through words. We also communicate with others through words. While words play a central role in human information processing, linguistic models are not often used in the fields of classification and modeling. If there is no goal other than the maximization of accuracy in classification and modeling, mathematical models may always be preferred to linguistic models. On the other hand, linguistic models may be chosen if emphasis is placed on interpretability.

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Classification and Learning Using Genetic Algorithms : Applications in Bioinformatics and Web Intelligence

This book provides a unified framework that describes how genetic learning can be used to design pattern recognition and learning systems. The book is unique in the sense of describing how a search technique, the genetic algorithm, can be used for pattern classification mainly through approximating decision boundaries, and it demonstrates the effectiveness of the genetic classifiers vis-à-vis several widely used classifiers, including neural networks. It provides a balanced mixture of theories, algorithms and applications, and in particular results from the bioinformatics and Web intelligence domains.

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Chinese Spoken Language, Processing ; 5th International Symposium, ISCSLP 2006, Singapore, December 13-16, 2006, Proceedings

This book contains a selection of refereed papers presented at the Fifth Inter- tionalSymposium on Chinese Spoken Language Processing(ISCSLP 2006), held in Singapore during December 13-16, 2006. ISCSLP is a biennial conference for scientists, researchers, and practitionersto reportand discuss the latest progress in all scientifc and technological aspects of Chinese spoken language processing (CSLP). The previous four conferences were held in Singapore (ISCSLP 1998), Beijing (ISCSLP 2000), Taipei (ISCSLP 2002) and Hong Kong (ISCSLP 2004), respectively.

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Chinese Computational Linguistics ; 19th China National Conference, CCL 2020, Hainan, China, October 30 – November 1, 2020, Proceedings

This book constitutes the proceedings of the 19th China National Conference on Computational Linguistics, CCL 2020, held in Hainan, China, in October/November 2020. The 32 full and 2 short papers presented in this volume were carefully reviewed and selected from 99 submissions. They were organized in topical sections named: fundamental theory and methods of computational linguistics; information retrieval, dialogue and question answering; text generation and summarization; knowledge graph and information extraction; machine translation and multilingual information processing; minority language information processing; language resource and evaluation; social computing and sentiment analysis; and NLP applications.

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Chemogenomics : Methods and protocols

Presents both theoretical guidance and protocols on chemogenomics including chemogenomics library assembly, compound profiling, and phenotypic assays. The chapters in this book cover topics such as the assembly and use of Kinase Chemogenomics; data mining for chemogenomic compound candidates; protocols for protein family-focused assay systems to profile chemogenomic compounds; functional and target engagement assays in cellular settings for broad characterization; and a discussion on phenotypic assays where chemogenomic sets may be applied.

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Chance Discoveries in Real World Decision Making : Data-based Interaction of Human intelligence and Artificial Intelligence

For this book, the editors invited and called for contributions from indispensable research areas relevant to "chance discovery," which has been defined as the discovery of events significant for making a decision, and studied since 2000. From respective research areas as artificial intelligence, mathematics, cognitive science, medical science, risk management, methodologies for design and communication, the invited and selected authors in this book present their particular approaches to chance discovery. The chapters here show contributions to identifying rare or hidden events and explaining their significance, predicting future trends, communications for scenario development in marketing and design, identification effects and side-effects of medicines, etc.

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Business process management Workshops ; BPM 2007 International Workshops, BPI, BPD, CBP, ProHealth, RefMod, semantics4ws, Brisbane, Australia, September 24, 2007, Revised Selected Papers

This book constitutes the thoroughly refereed post-workshop proceedings of 6 internationl workshops held in Brisbane, Australia, in conjunction with the 5th International Conference on Business Process Management, BPM 2007, in September 2007.

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Biomedical data mining for information retrieval : Methodologies, techniques, and applications

Discusses data mining, biomedical image processing, information retrieval with broad coverage of basic scientific applications. covers the topic of mining biomedical text, images and visual features towards information retrieval. Biomedical and health informatics is an emerging field of research at the intersection of information science, computer science, and healthcare and brings tremendous opportunities and challenges due to easily available and abundant biomedical data for further analysis. The aim of healthcare informatics is to ensure the high-quality, efficient healthcare, better treatment and quality of life by analyzing biomedical and healthcare data including patient’s data, electronic health records (EHRs) and lifestyle. Previously, it was a common requirement to have a domain expert to develop a model for biomedical or healthcare; however, recent advancements in representation learning algorithms allows us to automatically to develop the model. Biomedical image mining, a novel research area, due to the vast amount of available biomedical images, increasingly generates and stores digitally.

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Biomarkers in drug discovery and development : A handbook of practice, application, and strategy

Discusses biomarker characterization and validation and applications throughout drug discovery and development. Explains where proper use of biomarkers can substantively impact drug development timelines and costs, enable selection of better compounds and reduce late stage attrition, and facilitate personalized medicine. Helps readers get a better understanding of biomarkers and how to use them, for example which are accepted by regulators and which still non-validated and exploratory. Updates developments in genomic sequencing, and application of large data sets into pre-clinical and clinical testing; and adds new material on data mining, economics, and decision making, personal genetic tools, and wearable monitoring. Includes case studies of biomarkers that have helped and hindered decision making

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Biological and medical data analysis ; Vol. 3745 ; 6th International symposium, ISBMDA 2005, Aveiro, Portugal, November 10-11, 2005, Proceedings

The 6th International Symposium on Biological and Medical Data Analysisaimed to become a place where researchersinvolved in these diverse but increas-ingly complementary areas could meet topresent and discuss their scientificresults.The papers in this volume discuss issues from statistical models to archi-tectures and applications to bioinformatics and biomedicine. They cover bothpractical experience and novel research ideas and concepts.

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Biological and artificial intelligence environments

The book reports the proceedings of the 15th Italian workshop on neural networks issued by the Italian Society on Neural Networks SIREN. The longevity recipe of this conference stands in three main points that normally renders the reading of these proceedings so interesting as appealing. 1. The topics of the neural networks is considered an attraction pole for a set of researches centered on the inherent paradigm of the neural networks, rather than on a specific tool exclusively. Thus, the subsymbolic management of the data information content constitutes the key feature of papers in various fields such as Pattern Recognition, Stochastic Optimization, Learning, Granular Computing, and so on, with a special bias toward bioinformatics operational applications. An excerpt of all these matters may be found in the book. 2. Though managed at domestic level, the conference attracts contributions from foreign researchers as well, so that in the book the reader may capture the flavor of the state of the art in the international community. 3. The conference is a meeting of friends as well. Thus the papers generally reflect a relaxed atmosphere where researchers meet to generously exchange their thought and explain their actual results in view of a common cultural growing of the community.

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Bioinformatics technologies

Solving modern biological problems requires advanced computational methods. Bioinformatics evolved from the active interaction of two fast-developing disciplines, biology and information technology. The central issue of this emerging field is the transformation of often distributed and unstructured biological data into meaningful information. This book describes the application of well-established concepts and techniques from areas like data mining, machine learning, database technologies, and visualization techniques to problems like protein data analysis, genome analysis and sequence databases. Chen has collected contributions from leading researchers in each area. The chapters can be read independently, as each offers a complete overview of its specific area, or, combined, this monograph is a comprehensive treatment that will appeal to students, researchers, and R&D professionals in industry who need a state-of-the-art introduction into this challenging and exciting young field.

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Bioinformatics research and development ; 2nd International Conference, BIRD 2008 Vienna, Austria, July 7-9, 2008 Proceedings

This book constitutes the refereed proceedings of the Second International Bioinformatics Research and Development Conference, BIRD 2008, held in Vienna, Austria in July 2008.

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Bioinformatics research and applications : 4th International Symposium, ISBRA 2008, Atlanta, GA, USA, May 6-9, 2008. Proceedings

This book constitutes the refereed proceedings of the Fourth International Symposium on Bioinformatics Research and Applications, ISBRA 2008, held in Atlanta, GA, USA in May 2008.

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Bioinformatics of genome regulation and structure II

The conference was organized by the Laboratory of Theoretical Genetics, Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia. The material covers the most recent topics in bioinformatics, including (i) regulatory genomic sequences: databases, knowledge bases, computer analysis, modeling, and recognition; (ii) large-scale genome analysis and functional annotation; (iii) gene structure detection and prediction; (iv) comparative and evolutionary genomics; (v) computer analysis of genome polymorphism and evolution; computer analysis and modeling of transcription, splicing, and translation; structural computational biology: structure- function organization of genomic DNA, RNA, and proteins; (vi) gene networks, signal transduction pathways, and genetically controlled metabolic pathways: databases, knowledge bases, computer analysis, and modeling; principles of organization, operation, and evolution; (vii) data warehousing, knowledge discovery and data mining; and (viii) analysis of basic patterns of genome operation, organization, and evolution.

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Big Data in Energy Economics

Combines energy economics and big data modeling analysis in energy conversion and management and comprehensively introduces the relevant theories, key technologies, and application examples of the smart energy economy. With the help of time series big data modeling results, energy economy managers develop reasonable and feasible pricing mechanisms of electricity price and improve the absorption capacity of the power grid. In addition, they also carry out scientific power equipment scheduling and cost–benefit analysis according to the results of data mining, so as to avoid the loss caused by accidental damage of equipment. Energy users adjust their power consumption behavior through the modeling results provided and achieve the effect of energy saving and emission reduction while reasonably reducing the electricity expenditure.

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