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Chaos in Real Data, J.N. Perry; R.H. Smith; I.P. Woiwod; D.R. Morse


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Цена: 204040.00T
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Автор: J.N. Perry; R.H. Smith; I.P. Woiwod; D.R. Morse
Название:  Chaos in Real Data
ISBN: 9780412796906
Издательство: Springer
Классификация:
ISBN-10: 0412796902
Обложка/Формат: Hardcover
Страницы: 226
Вес: 0.52 кг.
Дата издания: 31.05.2000
Серия: Population and Community Biology Series
Язык: English
Размер: 234 x 156 x 14
Основная тема: Life Sciences
Подзаголовок: The Analysis of Non-Linear Dynamics from Short Ecological Time Series
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: Covering non-linear population dynamics, and in particular the estimation of the parameters of the underlying dynamical process. The text looks at the development of techniques of estimation for short ecological time-series where the number of generations ranges typically from 20 to 70.

A Practical Approach to Microarray Data Analysis

Автор: Berrar Daniel P., Dubitzky Werner, Granzow Martin
Название: A Practical Approach to Microarray Data Analysis
ISBN: 1402072600 ISBN-13(EAN): 9781402072604
Издательство: Springer
Рейтинг:
Цена: 32600.00 T
Наличие на складе: Есть
Описание: A Practical Approach to Microarray Data Analysis is for all life scientists, statisticians, computer experts, technology developers, managers, and other professionals tasked with developing, deploying, and using microarray technology including the necessary computational infrastructure and analytical tools. The book addresses the requirement of scientists and researchers to gain a basic understanding of microarray analysis methodologies and tools. It is intended for students, teachers, researchers, and research managers who want to understand the state of the art and of the presented methodologies and the areas in which gaps in our knowledge demand further research and development. The book is designed to be used by the practicing professional tasked with the design and analysis of microarray experiments or as a text for a senior undergraduate- or graduate level course in analytical genetics, biology, bioinformatics, computational biology, statistics and data mining, or applied computer science. Key topics covered include: -Format of result from data analysis, analytical modeling/experimentation; -Validation of analytical results; -Data analysis/Modeling task; -Analysis/modeling tools; -Scientific questions, goals, and tasks; -Application; -Data analysis methods; -Criteria for assessing analysis methodologies, models, and tools.

New Advances in Statistics and Data Science

Автор: Ding-Geng Chen; Zhezhen Jin; Gang Li; Yi Li; Aiyi
Название: New Advances in Statistics and Data Science
ISBN: 3319694154 ISBN-13(EAN): 9783319694153
Издательство: Springer
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Цена: 71730.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The theme of this conference was the "Challenge of Big Data and Applications of Statistics," in recognition of the advent of big data era, and the symposium offered opportunities for learning, receiving inspirations from old research ideas and for developing new ones, and for promoting further research collaborations in the data sciences.

Bayesian Data Analysis in Ecology Using Linear Models with R, BUG

Автор: Franzi Korner-Nievergelt
Название: Bayesian Data Analysis in Ecology Using Linear Models with R, BUG
ISBN: 0128013702 ISBN-13(EAN): 9780128013700
Издательство: Elsevier Science
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Цена: 66240.00 T
Наличие на складе: Невозможна поставка.
Описание:

Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and STAN examines the Bayesian and frequentist methods of conducting data analyses. The book provides the theoretical background in an easy-to-understand approach, encouraging readers to examine the processes that generated their data. Including discussions of model selection, model checking, and multi-model inference, the book also uses effect plots that allow a natural interpretation of data. Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and STAN introduces Bayesian software, using R for the simple modes, and flexible Bayesian software (BUGS and Stan) for the more complicated ones. Guiding the ready from easy toward more complex (real) data analyses ina step-by-step manner, the book presents problems and solutions--including all R codes--that are most often applicable to other data and questions, making it an invaluable resource for analyzing a variety of data types.


Healthcare and Big Data Management

Автор: Bairong Shen
Название: Healthcare and Big Data Management
ISBN: 9811060401 ISBN-13(EAN): 9789811060403
Издательство: Springer
Рейтинг:
Цена: 139750.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The book addresses the interplay of healthcare and big data management. Thanks to major advances in big data technologies and precision medicine, healthcare is now becoming the new frontier for both scientific research and economic development. This volume covers a range of aspects, including: big data management for healthcare;

Complexity, Chaos, and Biological Evolution

Автор: Erik Mosekilde; Lis Mosekilde
Название: Complexity, Chaos, and Biological Evolution
ISBN: 1468478494 ISBN-13(EAN): 9781468478495
Издательство: Springer
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Цена: 46570.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Proceedings of a NATO ARW on Complex Dynamics and Biological Evolution, held in Hindsgavl, Denmark, August 6--10, 1990

Microarray Data Analysis

Автор: Pietro Hiram Guzzi
Название: Microarray Data Analysis
ISBN: 1493931725 ISBN-13(EAN): 9781493931729
Издательство: Springer
Рейтинг:
Цена: 130610.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:

Di Wu and Michael P. Gantier

2) Methods and Techniques for miRNA Data Analysis

Francesca Cristiano and Pierangelo Veltri

3) Bioinformatics and Microarray Data Analysis on The Cloud

Barbara Calabrese and Mario Cannataro

4) Classification and Clustering on Microarray Data for Gene Functional Prediction using R

Liliana Lуpez Kleine, Rosa Montaсo, and Francisco Torres-Avilйs

5) Querying co-regulated genes on diverse gene expression datasets via biclustering

Mehmet Deveci, Onur Kucuktunc, Kernal Eren, Doruk Bozadag, Kamer Kaya, and Umit V. Catalyurek

6) MetaMirClust: Discovery and Exploration of Evolutionarily Conserved miRNA Clusters

Wen-Ching Chan and Wen-chang Lin

7) Analysis of Gene Expression Patterns using Biclustering

Swarup Roy, Dhruba K Bhattacharyya, and Jugal K Kalita

8) Using semantic Similarities and csbl.go for Analyzing Microarray Data

Kristian Ovaska

9) Ontology Based Analysis of Microarray Data

Giuseppe Agapito and Marianna Milano

10) Integrated Analysis of Transcriptomic and Proteomic Datasets Reveals Information on Protein Expressivity and Factors Affecting Translational Efficiency

Jiangxin Wang, Gang Wu, Lei Chen, and Weiwen Zhang

11) Integrating Microarray Data and GRNs

L. Koumakis, G. Potamias, M. Tsiknakis, M. Zervakis, and V. Moustakis

12) Biological Network Inference from Microarray Data, Current Solutions and Assessments

Swarup Roy and Pietro Hiram Guzzi

13) A Protocol to Collect Specific Mouse Skeletal Muscles for Metabolomics Studies

Zhuohui Gan, Zhenxing Fu, Jennifer C. Stowe, Frank L. Powell, and Andrew D. McCulloch

14) Functional Analysis of microRNA in Multiple Myeloma

Maria Teresa Di Martino, Nicola Amodio, Pierfrancesco Tassone, and Pierosandro Tagliaferri

15) Microarray Analysis in Glioblastomas

Kaumudi M. Bhawe and Manish K. Aghi

16) Analysis of microRNA Microarrays in Cardiogenesis

Diego Franco, Fernando Bonet, Francisco Hernandez-Torres, Estefania Lozano-Velasco, Francisco Esteban, and Amelia E Aranega


Chaos in Real Data

Автор: J.N. Perry; R.H. Smith; I.P. Woiwod; D.R. Morse
Название: Chaos in Real Data
ISBN: 9401057729 ISBN-13(EAN): 9789401057721
Издательство: Springer
Рейтинг:
Цена: 93160.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Chaos in Real Data studies the range of data analytic techniques available to study nonlinear population dynamics for ecological time series. Several case studies are studied using typically short and noisy population data from field and laboratory.


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