Identifiability and Regression Analysis of Biological Systems Models (Record no. 64851)
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| fixed length control field | 04073nam a22005535i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-3-031-74748-9 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | DE-He213 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20251030113306.0 |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION | |
| fixed length control field | cr nn 008mamaa |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 241110s2024 sz | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9783031747489 |
| -- | 978-3-031-74748-9 |
| 024 7# - OTHER STANDARD IDENTIFIER | |
| Standard number or code | 10.1007/978-3-031-74748-9 |
| Source of number or code | doi |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER | |
| Classification number | QH323.5 |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | PBT |
| Source | bicssc |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | MED090000 |
| Source | bisacsh |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | PBT |
| Source | thema |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Lecca, Paola. |
| Relator term | author. |
| Relator code | aut |
| -- | http://id.loc.gov/vocabulary/relators/aut |
| 9 (RLIN) | 87301 |
| 245 10 - TITLE STATEMENT | |
| Title | Identifiability and Regression Analysis of Biological Systems Models |
| Medium | [electronic resource] : |
| Remainder of title | Statistical and Mathematical Foundations and R Scripts / |
| Statement of responsibility, etc. | by Paola Lecca. |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 2nd ed. 2024. |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE | |
| Place of production, publication, distribution, manufacture | Cham : |
| Name of producer, publisher, distributor, manufacturer | Springer Nature Switzerland : |
| -- | Imprint: Springer, |
| Date of production, publication, distribution, manufacture, or copyright notice | 2024. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | XII, 124 p. 26 illus., 16 illus. in color. |
| Other physical details | online resource. |
| 336 ## - CONTENT TYPE | |
| Content type term | text |
| Content type code | txt |
| Source | rdacontent |
| 337 ## - MEDIA TYPE | |
| Media type term | computer |
| Media type code | c |
| Source | rdamedia |
| 338 ## - CARRIER TYPE | |
| Carrier type term | online resource |
| Carrier type code | cr |
| Source | rdacarrier |
| 347 ## - DIGITAL FILE CHARACTERISTICS | |
| File type | text file |
| Encoding format | |
| Source | rda |
| 490 1# - SERIES STATEMENT | |
| Series statement | SpringerBriefs in Statistics, |
| International Standard Serial Number | 2191-5458 |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Formatted contents note | - 1. Complex Systems, Data and Inference -- 2. Dynamic Models -- 3. Model Identifiability -- 4. Regression and Variable Selection -- 5. Parameter Estimation using Artificial Intelligence -- 6. R Scripts. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | This richly illustrated book presents the latest techniques for the identifiability analysis and standard and robust regression analysis of complex dynamical models, and looks at their objectives. It begins by providing a definition of complexity in dynamic systems, introducing the concepts of system size, density of interactions, stiff dynamics, and the hybrid nature of determination. The discussion then turns to the mathematical foundations of model structural and practical identifiability analysis, multilinear and non-linear regression analysis, and best predictor selection, and their algorithmic procedures. Although the featured examples mainly focus on applications to biochemistry and systems biology, the methodologies described can also be employed in other disciplines such as physics and the environmental sciences. Readers will learn how to determine identifiability conditions, how to search for an identifiable model, and how to conduct their own regression analysis and diagnostics without supervision. This new edition includes a concise, yet comprehensive treatment of the main artificial intelligence methods which can be used for parameter inference in models of complex dynamic biological systems. It emphasizes the most efficient solutions for generating synthetic data that augment the training data and which are indispensable for machine learning procedures. Featuring a wealth of real-world examples, exercises, and R codes, the book addresses the needs of doctoral students and researchers in bioinformatics, bioengineering, systems biology, biophysics, biochemistry, the environmental sciences and experimental physics. Familiarity with the fundamentals of probability and statistics (as provided in first-year university courses) and a basic grasp of R are assumed. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | |
| 9 (RLIN) | 65981 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | |
| 9 (RLIN) | 64050 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | |
| 9 (RLIN) | 65982 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | |
| 9 (RLIN) | 70325 |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | |
| 9 (RLIN) | 65985 |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | |
| 9 (RLIN) | 65974 |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | |
| 9 (RLIN) | 70327 |
| 710 2# - ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | SpringerLink (Online service) |
| 773 0# - HOST ITEM ENTRY | |
| Title | Springer Nature eBook |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
| Relationship information | Printed edition: |
| International Standard Book Number | 9783031747472 |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
| Relationship information | Printed edition: |
| International Standard Book Number | 9783031747496 |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
| Uniform title | SpringerBriefs in Statistics, |
| International Standard Serial Number | 2191-5458 |
| 9 (RLIN) | 84859 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | <a href="https://doi.org/10.1007/978-3-031-74748-9">https://doi.org/10.1007/978-3-031-74748-9</a> |
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| -- | ZDB-2-SMA |
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| -- | ZDB-2-SXMS |
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