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Titlebook: Biomedical Data and Applications; Amandeep S. Sidhu,Tharam S. Dillon Book 2009 Springer-Verlag Berlin Heidelberg 2009 algorithm.bioinforma

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發(fā)表于 2025-3-21 20:09:47 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Biomedical Data and Applications
影響因子2023Amandeep S. Sidhu,Tharam S. Dillon
視頻videohttp://file.papertrans.cn/189/188006/188006.mp4
發(fā)行地址Presents recent results connected to biomedical data and applications
學科分類Studies in Computational Intelligence
圖書封面Titlebook: Biomedical Data and Applications;  Amandeep S. Sidhu,Tharam S. Dillon Book 2009 Springer-Verlag Berlin Heidelberg 2009 algorithm.bioinforma
影響因子.Compared with data from general application domains, modern biological data has many unique characteristics. Biological data are often characterized as having large volumes, complex structures, high dimensionality, evolving biological concepts, and insufficient data modelling practices. Over the past several years, bioinformatics has become an all-encompassing term for everything relating to both computer science and biology. The goal of this book is to cover data and applications identifying new issues and directions for future research in biomedical domain. The book will become a useful guide learning state-of-the-art development in biomedical data management, data-intensive bioinformatics systems, and other miscellaneous biological database applications. The book addresses various topics in bioinformatics with varying degrees of balance between biomedical data models and their real-world applications..
Pindex Book 2009
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發(fā)表于 2025-3-21 23:16:29 | 只看該作者
Towards Bioinformatics Resourceomes bioinformatics as a very dynamic universe, continuously growing under our eyes. More and more scientists are approaching it and would like to easier explore it, discovering the resources that can be found in every space region (i.e. related to every bioinformatics topic). We propose to intuitively
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A Summary of Genomic Databases: Overview and Discussionoday, more than eight hundred can be counted thereof). In spite of the enormous amount of available resources, a user may be disoriented when he/she searches for specific data. Thus, the accurate analysis of biological data and repositories turn out to be useful to obtain a systematic view of biolog
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發(fā)表于 2025-3-22 04:59:58 | 只看該作者
Protein Data Integration Problemas an integral part of their discovery process. Specifically, data integration, meta-data specification, data provenance and data quality, and ontology are discussed here. These are the fundamental problems that need to be solved by the bioinformatics community so that modern information technology
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Bio-medical Ontologies Maintenance and Change Managementseveral techniques from areas such as knowledge representation, semantic web and databases. Many of these techniques require a formal description of a part of the real world. Ontologies can provide a set of shared and precisely defined terms in various degrees of formality to describe a particular d
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發(fā)表于 2025-3-22 17:32:10 | 只看該作者
Extraction of Constraints from Biological Datacontext, a constraint can be defined as a set of predicates P.?∧?P.?∧?... P.. Each predicate is in the form C..C., where C. is an attribute, . is a comparison operator and C. is either an attribute or a constant [15]. Constraints are assertions on permissible or consistent database states, and speci
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發(fā)表于 2025-3-23 05:43:22 | 只看該作者
Substructure Analysis of Metabolic Pathways by Graph-Based Relational Learningips is a fundamental way to represent a bio-system. A graph consisting of vertices and edges between these vertices is a natural data structure to represent biological networks. Substructure analysis of metabolic pathways by graph-based relational learning provides us biologically meaningful substru
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