By Mihail Popescu, Dong Xu
An ontology is a collection of vocabulary phrases with explicitly said meanings and kin with different phrases. almost immediately, more and more ontologies are being equipped and used for annotating facts in biomedical learn. because of the large volume of knowledge being generated, ontologies are actually getting used in different methods, together with connecting diverse databases, refining seek services, reading experimental/clinical information, and inferring wisdom. This state of the art source introduces researchers to most up-to-date advancements in bio-ontologies. The ebook presents the theoretical foundations and examples of ontologies, in addition to purposes of ontologies in biomedicine, from molecular degrees to medical degrees. Readers additionally locate info on technological infrastructure for bio-ontologies. This finished, one-stop quantity provides a variety of useful bio-ontology info, providing execs specific counsel within the clustering of organic information, protein category, gene and pathway prediction, and textual content mining.
Read Online or Download Data Mining in Biomedicine Using Ontologies (Artech House Series Bioinformatics & Biomedical Imaging) PDF
Best data mining books
Information mining is anxious with the research of databases sufficiently big that numerous anomalies, together with outliers, incomplete facts files, and extra refined phenomena corresponding to misalignment blunders, are almost sure to be current. Mining Imperfect facts: facing infection and Incomplete documents describes intimately a couple of those difficulties, in addition to their assets, their outcomes, their detection, and their remedy.
A brand new unsupervised method of the matter of knowledge Extraction through textual content Segmentation (IETS) is proposed, applied and evaluated herein. The authors’ technique depends upon info on hand on pre-existing facts to benefit tips to affiliate segments within the enter string with attributes of a given area counting on a really powerful set of content-based good points.
The six-volume set LNCS 8579-8584 constitutes the refereed complaints of the 14th foreign convention on Computational technology and Its purposes, ICCSA 2014, held in Guimarães, Portugal, in June/July 2014. The 347 revised papers provided in 30 workshops and a different music have been rigorously reviewed and chosen from 1167.
Cristobal Romero, Sebastian Ventura, Mykola Pechenizkiy and Ryan S. J. d. Baker, «Handbook of academic information Mining» . instruction manual of academic facts Mining (EDM) presents a radical evaluation of the present kingdom of information during this quarter. the 1st a part of the e-book contains 9 surveys and tutorials at the imperative information mining suggestions which were utilized in schooling.
- Principles of Data Mining (2nd Edition) (Undergraduate Topics in Computer Science)
- Data Mining: The Textbook
Additional info for Data Mining in Biomedicine Using Ontologies (Artech House Series Bioinformatics & Biomedical Imaging)
Cimino, J. , and X. Zhu, “The Practical Impact of Ontologies on Biomedical Informatics,” Methods Inf Med, Vol. 45, Supplement 1, 2006, pp. 124–135. , “The GOA Database in 2009—An Integrated Gene Ontology Annotation Resource,” Nucl. , Vol. 37, Supplement 1, 2009, pp. D396–D403. , “The Compositional Structure of Gene Ontology Terms,” Pac Symp Biocomput, 2004, p. 214–225. Mungall, C. , “Obol: Integrating Language and Meaning in Bio-Ontologies,” Comparative and Functional Genomics, Vol. 5, Nos. 6–7, 2004, pp.
This similarity measure, 30 Ontological Similarity Measures however, is not actually an ontological similarity measure in the traditional sense, since it does not assess similarity between concepts in an ontology. Instead, it determines overall similarity between objects described by ontological concepts. One version of the fuzzy-measure-based ontological similarity, SAFMS, augments the sets X and Y with the lowest or nearest common ancestor of every pair (xi, yj). For more details on the use of the fuzzy-measure-based approach to assessing similarity between gene products, see .
This is the principle success of the GO, but the use of ontologies as drivers for integration at either the level of schema or the level of the values in the schema are long-standing within bioinformatics and computer science . 6) were early examples. Once data is described, it can be queried and analyzed in terms of its biological meaning, providing new aspects for looking into the data. As biology is often portrayed as a descriptive science, the role of ontologies in bioinformatics will undoubtedly continue.