Understanding the Functionality of a Biological System as a Whole: Comparative Data Analysis

2018 ◽  
pp. 311-319
Author(s):  
Isabel Orf
Keyword(s):  
Data Analysis ◽  
Biological System ◽  
Comparative Data

QuanTP: A Software Resource for Quantitative Proteo-Transcriptomic Comparative Data Analysis and Informatics

2018 ◽  
Vol 18 (2) ◽  
pp. 782-790 ◽  
Author(s):  
Praveen Kumar ◽  
Priyabrata Panigrahi ◽  
James Johnson ◽  
Wanda J. Weber ◽  
Subina Mehta ◽  
...  
Keyword(s):  
Data Analysis ◽  
Comparative Data

Data Analysis and Interpretation in Metabolomics

2013 ◽  
pp. 1494-1521
Author(s):  
Jose M. Garcia-Manteiga
Keyword(s):  
Mass Spectrometry ◽  
Nuclear Magnetic Resonance ◽  
Data Analysis ◽  
Systems Biology ◽  
Magnetic Resonance ◽  
Biological System ◽  
Analytical Techniques ◽  
Point Of View ◽  
The Other ◽  
Top Down

Metabolomics represents the new ‘omics’ approach of the functional genomics era. It consists in the identification and quantification of all small molecules, namely metabolites, in a given biological system. While metabolomics refers to the analysis of any possible biological system, metabonomics is specifically applied to disease and physiopathological situations. The data collected within these approaches is highly integrative of the other higher levels and is hence amenable to be explored with a top-down systems biology point of view. The aim of this chapter is to give a global view of the state of the art in metabolomics describing the two analytical techniques usually used to give rise to this kind of data, nuclear magnetic resonance, NMR, and mass spectrometry. In addition, the author will focus on the different data analysis tools that can be applied to such studies to extract information with special interest at the attempts to integrate metabolomics with other ‘omics’ approaches and its relevance in systems biology modeling.

Data Analysis and Interpretation in Metabolomics

2011 ◽  
pp. 29-56
Author(s):  
Jose M. Garcia-Manteiga
Keyword(s):  
Mass Spectrometry ◽  
Nuclear Magnetic Resonance ◽  
Data Analysis ◽  
Systems Biology ◽  
Magnetic Resonance ◽  
Biological System ◽  
Analytical Techniques ◽  
Point Of View ◽  
The Other ◽  
Top Down

Metabolomics represents the new ‘omics’ approach of the functional genomics era. It consists in the identification and quantification of all small molecules, namely metabolites, in a given biological system. While metabolomics refers to the analysis of any possible biological system, metabonomics is specifically applied to disease and physiopathological situations. The data collected within these approaches is highly integrative of the other higher levels and is hence amenable to be explored with a top-down systems biology point of view. The aim of this chapter is to give a global view of the state of the art in metabolomics describing the two analytical techniques usually used to give rise to this kind of data, nuclear magnetic resonance, NMR, and mass spectrometry. In addition, the author will focus on the different data analysis tools that can be applied to such studies to extract information with special interest at the attempts to integrate metabolomics with other ‘omics’ approaches and its relevance in systems biology modeling.

scholarly journals Assisted Descriptor Selection Based on Visual Comparative Data Analysis

2011 ◽  
Vol 30 (3) ◽  
pp. 891-900 ◽  
Author(s):  
Sebastian Bremm ◽  
Tatiana von Landesberger ◽  
Jürgen Bernard ◽  
Tobias Schreck
Keyword(s):  
Data Analysis ◽  
Comparative Data ◽  
Descriptor Selection

scholarly journals Initial Implementation of a Comparative Data Analysis Ontology

2009 ◽  
Vol 5 ◽  
pp. EBO.S2320 ◽  
Author(s):  
Francisco Prosdocimi ◽  
Brandon Chisham ◽  
Enrico Pontelli ◽  
Julie D. Thompson ◽  
Arlin Stoltzfus
Keyword(s):  
Data Analysis ◽  
Comparative Data ◽  
Initial Implementation

scholarly journals Transatlantic combined and comparative data analysis of 1095 patients with urea cycle disorders—A successful strategy for clinical research of rare diseases

2019 ◽  
Vol 42 (1) ◽  
pp. 93-106 ◽  
Author(s):  
Roland Posset ◽  
Sven F. Garbade ◽  
Nikolas Boy ◽  
Alberto B. Burlina ◽  
Carlo Dionisi‐Vici ◽  
...  
Keyword(s):  
Data Analysis ◽  
Clinical Research ◽  
Rare Diseases ◽  
Urea Cycle ◽  
Comparative Data ◽  
Urea Cycle Disorders ◽  
Successful Strategy ◽  
Cycle Disorders

Knowledge Standardization in Evolutionary Biology: The Comparative Data Analysis Ontology

2009 ◽  
pp. 195-214 ◽  
Author(s):  
Francisco Prosdocimi ◽  
Brandon Chisham ◽  
Enrico Pontelli ◽  
Arlin Stoltzfus ◽  
Julie D. Thompson
Keyword(s):  
Data Analysis ◽  
Evolutionary Biology ◽  
Comparative Data

Radial visualizations for comparative data analysis

2012 ◽  
Author(s):  
Geoffrey M. Draper ◽  
Matthew G. Styles ◽  
Richard F. Riesenfeld
Keyword(s):  
Data Analysis ◽  
Comparative Data
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