Association Analysis Techniques and Applications in Bioinformatics (Record no. 87911)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 04481nam a22006135i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-981-99-8251-6 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20240730171941.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 240425s2024 si | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9789819982516 |
| -- | 978-981-99-8251-6 |
| 082 04 - CLASSIFICATION NUMBER | |
| Call Number | 006.312 |
| 100 1# - AUTHOR NAME | |
| Author | Chen, Qingfeng. |
| 245 10 - TITLE STATEMENT | |
| Title | Association Analysis Techniques and Applications in Bioinformatics |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 1st ed. 2024. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | XXI, 388 p. 116 illus., 58 illus. in color. |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Remark 2 | Chapter1:Computer science for Molecular biology -- Chapter2:Introduction to association analysis -- Chapter3:Introduction to computational linguistics and biology structure -- Chapter4:Matrix decomposition for dimensionality deduction -- Chapter5:Discovering conserved RNA secondary structures with structure similarity -- Chapter6:Gene ontology for non-coding RNAs classification -- Chapter7:Learning frequent sub-structure by graph mining -- Chapter8:Editing distance and its application to biology graph analytics -- Chapter9:Sequence assembly and applications -- Chapter10:Classifying protein structures by measuring structural similarity -- Chapter11:Identification of metabolic pathways with embedding network -- Chapter12:Emerging Knowledge integration-based approach with multi-sources data for bioinformatics -- Chapter13:Conclusion and Future Work. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | Advances in experimental technologies have given rise to tremendous amounts of biology data. This not only offers valuable sources of data to help understand biological evolution and functional mechanisms, but also poses challenges for accurate and effective data analysis. This book offers an essential introduction to the theoretical and practical aspects of association analysis, including data pre-processing, data mining methods/algorithms, and tools that are widely applied for computational biology. It covers significant recent advances in the field, both foundational and application-oriented, helping readers understand the basic principles and emerging techniques used to discover interesting association patterns in diverse and heterogeneous biology data, such as structure-function correlations, and complex networks with gene/protein regulation. The main results and approaches are described in an easy-to-follow way and accompanied by sufficient references and suggestions for future research. This carefully edited monograph is intended to provide investigators in the fields of data mining, machine learning, artificial intelligence, and bioinformatics with a profound guide to the role of association analysis in computational biology. It is also very useful as a general source of information on association analysis, and as an overall accompanying course book and self-study material for graduate students and researchers in both computer science and bioinformatics. . |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | https://doi.org/10.1007/978-981-99-8251-6 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks |
| 264 #1 - | |
| -- | Singapore : |
| -- | Springer Nature Singapore : |
| -- | Imprint: Springer, |
| -- | 2024. |
| 336 ## - | |
| -- | text |
| -- | txt |
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| -- | computer |
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| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
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| -- | rdacarrier |
| 347 ## - | |
| -- | text file |
| -- | |
| -- | rda |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Data mining. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Expert systems (Computer science). |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Machine learning. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Bioinformatics. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Big data. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Medical informatics. |
| 650 14 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Data Mining and Knowledge Discovery. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Knowledge Based Systems. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Machine Learning. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computational and Systems Biology. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Big Data. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Health Informatics. |
| 912 ## - | |
| -- | ZDB-2-SCS |
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| -- | ZDB-2-SXCS |
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