Outlines and Highlights for Data Mining for Genomics and Proteomics
Title | Outlines and Highlights for Data Mining for Genomics and Proteomics PDF eBook |
Author | Cram101 Textbook Reviews |
Publisher | Academic Internet Pub Incorporated |
Pages | 104 |
Release | 2011-04 |
Genre | Computers |
ISBN | 9781614613671 |
Never HIGHLIGHT a Book Again! Virtually all of the testable terms, concepts, persons, places, and events from the textbook are included. Cram101 Just the FACTS101 studyguides give all of the outlines, highlights, notes, and quizzes for your textbook with optional online comprehensive practice tests. Only Cram101 is Textbook Specific. Accompanys: 9780470163733 .
Fundamentals of Data Mining in Genomics and Proteomics
Title | Fundamentals of Data Mining in Genomics and Proteomics PDF eBook |
Author | Werner Dubitzky |
Publisher | Springer Science & Business Media |
Pages | 300 |
Release | 2007-04-13 |
Genre | Science |
ISBN | 0387475095 |
This book presents state-of-the-art analytical methods from statistics and data mining for the analysis of high-throughput data from genomics and proteomics. It adopts an approach focusing on concepts and applications and presents key analytical techniques for the analysis of genomics and proteomics data by detailing their underlying principles, merits and limitations.
Studyguide for Data Mining for Genomics and Proteomics
Title | Studyguide for Data Mining for Genomics and Proteomics PDF eBook |
Author | Cram101 Textbook Reviews |
Publisher | Cram101 |
Pages | 88 |
Release | 2013-05 |
Genre | |
ISBN | 9781490237183 |
Never HIGHLIGHT a Book Again Includes all testable terms, concepts, persons, places, and events. Cram101 Just the FACTS101 studyguides gives all of the outlines, highlights, and quizzes for your textbook with optional online comprehensive practice tests. Only Cram101 is Textbook Specific. Accompanies: 9780872893795. This item is printed on demand.
Rechnergestützte Konstruktionsarbeit
Title | Rechnergestützte Konstruktionsarbeit PDF eBook |
Author | Siegfried Schreuder |
Publisher | |
Pages | 187 |
Release | 1989 |
Genre | Computer-aided design |
ISBN | 9780387516608 |
Data Mining for Genomics and Proteomics
Title | Data Mining for Genomics and Proteomics PDF eBook |
Author | Darius M. Dziuda |
Publisher | John Wiley & Sons |
Pages | 348 |
Release | 2010-07-16 |
Genre | Computers |
ISBN | 0470593407 |
Data Mining for Genomics and Proteomics uses pragmatic examples and a complete case study to demonstrate step-by-step how biomedical studies can be used to maximize the chance of extracting new and useful biomedical knowledge from data. It is an excellent resource for students and professionals involved with gene or protein expression data in a variety of settings.
Data Analysis and Visualization in Genomics and Proteomics
Title | Data Analysis and Visualization in Genomics and Proteomics PDF eBook |
Author | Francisco Azuaje |
Publisher | John Wiley & Sons |
Pages | 284 |
Release | 2005-06-24 |
Genre | Science |
ISBN | 0470094400 |
Data Analysis and Visualization in Genomics and Proteomics is the first book addressing integrative data analysis and visualization in this field. It addresses important techniques for the interpretation of data originating from multiple sources, encoded in different formats or protocols, and processed by multiple systems. One of the first systematic overviews of the problem of biological data integration using computational approaches This book provides scientists and students with the basis for the development and application of integrative computational methods to analyse biological data on a systemic scale Places emphasis on the processing of multiple data and knowledge resources, and the combination of different models and systems
Introduction to Data Mining for the Life Sciences
Title | Introduction to Data Mining for the Life Sciences PDF eBook |
Author | Rob Sullivan |
Publisher | Springer Science & Business Media |
Pages | 644 |
Release | 2012-01-07 |
Genre | Science |
ISBN | 1597452904 |
Data mining provides a set of new techniques to integrate, synthesize, and analyze tdata, uncovering the hidden patterns that exist within. Traditionally, techniques such as kernel learning methods, pattern recognition, and data mining, have been the domain of researchers in areas such as artificial intelligence, but leveraging these tools, techniques, and concepts against your data asset to identify problems early, understand interactions that exist and highlight previously unrealized relationships through the combination of these different disciplines can provide significant value for the investigator and her organization.