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* Ontologies for Bioinformatics (Computational Molecular Biology) ✓ PDF Read by # Kenneth Baclawski, Tianhua Niu eBook or Kindle ePUB Online free. Ontologies for Bioinformatics (Computational Molecular Biology) George J. Shannon said Title can mislead: Greater focus on methods than content of ontologies. I was disappointed in this book in the lack of depth or breadth on a couple of key areas as follows:Item 1 - It appeared to me that ontologies were not explained in sufficient detail to help "newbies" determine exactly why a specific ontology was created and the specific functions it is designed to support. I'm considering the UMLS to prototype a search engine because it is a compilation of a number of
| Title | : | Ontologies for Bioinformatics (Computational Molecular Biology) |
| Author | : | |
| Rating | : | 4.60 (907 Votes) |
| Asin | : | 0262025914 |
| Format Type | : | paperback |
| Number of Pages | : | 440 Pages |
| Publish Date | : | 2015-09-25 |
| Language | : | English |
George J. Shannon said Title can mislead: Greater focus on methods than content of ontologies. I was disappointed in this book in the lack of depth or breadth on a couple of key areas as follows:Item 1 - It appeared to me that ontologies were not explained in sufficient detail to help "newbies" determine exactly why a specific ontology was created and the specific functions it is designed to support. I'm considering the UMLS to prototype a search engine because it is a compilation of a number of ontologies. However, this provides numerous options for subsetting the UMLS; for those relatively new to these ontologies it is not clear which ontology subsets are the most important (i.e., which play a
Kenneth Baclawski is Associate Professor of Computer Science at Northeastern University.Tianhua Niu is Assistant Professor of Psychiatry and Neurobehavioral Sciences in the Department of Psychiatry and Neurobehavioral Sciences at the University of Virginia School of Medicine.
Ontologies -- computer-readable, precise formulations of concepts (and the relationship among them) in a given field -- are a critical framework for coping with the exponential growth of valuable biological data generated by high-output technologies. They call this inductive reasoning web the Bayesian web.. They show how to construct and use ontologies, classifying uses into three categories: querying, viewing, and transforming data to serve diverse purposes. This book introduces the key concepts and applications of ontologies and ontology languages in bioinformatics and will be an essential guide for bioinformaticists, computer scientists, and life science researchers.The three parts of Ontologies for Bioinformatics ask, and answer, three pivotal questions: what ontologies are; how ontologies are used; and what ontologies could be (which focuses on how ontologies could be used for reasoning with uncertainty). The authors first introduce the notion of an ontology, from hierarchically organized ontologies to more general network organizations, and survey the best-known ontologies in biology and medicine. Contrasting deductive, or Boolean, logic with inductive reasoning, they describe the goal of a synthe
Ontology is the solution, and this book is an excellent effort to evaluate a number of alternative ontology-exchange languages, and to recommend them for use within the larger bioinformatics community. Ontology is the solution, and this book is an excellent effort to evaluate a number of alternative ontology-exchange languages, and to recommend them for use within the larger bioinformatics community."--Bo Yuan, Departments of Biomedical Informatics and Pharmacology, The Ohio State UniversityGiven the current explosion of biological data in multiple dimensions, it is time to think systematically about strategies and techniques to not only store, but also integrate and represent them in knowledge-oriented ways. (Bo Yuan, Depa
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