English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  Predicting physiological concentrations of metabolites from their molecular structure

Liebermeister, W. (2005). Predicting physiological concentrations of metabolites from their molecular structure. Journal of Computational Biology, 12(10), 1307-1315.

Item is

Basic

show hide
Genre: Journal Article
Alternative Title : J Comput Biol

Files

show Files
hide Files
:
Liebermeister - JCB.pdf (Any fulltext), 80KB
Name:
Liebermeister - JCB.pdf
Description:
-
OA-Status:
Visibility:
Public
MIME-Type / Checksum:
application/pdf / [MD5]
Technical Metadata:
Copyright Date:
-
Copyright Info:
eDoc_access: PUBLIC
License:
-

Locators

show

Creators

show
hide
 Creators:
Liebermeister, Wolfram1, Author
Affiliations:
1Max Planck Society, ou_persistent13              

Content

show
hide
Free keywords: metabolite concentration, QSPR, molecule structure, lasso regression
 Abstract: Physiological concentrations of metabolites can partly be explained by their molecular structure. We hypothesize that substances containing certain chemical groups show increased or decreased concentration in cells. We consider here, as chemical groups, local atomic configurations, describing an atom, its bonds, and its direct neighbor atoms. To test our hypothesis, we fitted a linear statistical model that relates experimentally determined logarithmic concentrations to feature vectors containing count numbers of the chemical groups. In order to determine chemical groups that have a clear effect on the concentration, we use a regularized (lasso) regression. In a dataset on 41 substances of central metabolism in different organisms, we found that the physical concentrations are increased by the occurrence of amino and hydroxyl groups, while aldehydes, ketones, and phosphates show decreased concentrations. The model explains about 22% of the variance of the logarithmic mean concentrations.

Details

show
hide
Language(s): eng - English
 Dates: 2005-12
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: eDoc: 272677
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Journal of Computational Biology
  Alternative Title : J Comput Biol
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: 12 (10) Sequence Number: - Start / End Page: 1307 - 1315 Identifier: ISSN: 1066-5277