Linked Life Data

19535531

Source:http://linkedlifedata.com/resource/pubmed/id/19535531

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
16
pubmed:dateCreated
2009-8-11
pubmed:abstractText
MOTIVATION: Distribution analysis is one of the most basic forms of statistical analysis. Thanks to improved analytical methods, accurate and extensive quantitative measurements can now be made of the mRNA, protein and metabolite from biological systems. Here, we report a large-scale analysis of the population abundance distributions of the transcriptomes, proteomes and metabolomes from varied biological systems. RESULTS: We compared the observed empirical distributions with a number of distributions: power law, lognormal, loglogistic, loggamma, right Pareto-lognormal (PLN) and double PLN (dPLN). The best-fit for mRNA, protein and metabolite population abundance distributions was found to be the dPLN. This distribution behaves like a lognormal distribution around the centre, and like a power law distribution in the tails. To better understand the cause of this observed distribution, we explored a simple stochastic model based on geometric Brownian motion. The distribution indicates that multiplicative effects are causally dominant in biological systems. We speculate that these effects arise from chemical reactions: the central-limit theorem then explains the central lognormal, and a number of possible mechanisms could explain the long tails: positive feedback, network topology, etc. Many of the components in the central lognormal parts of the empirical distributions are unidentified and/or have unknown function. This indicates that much more biology awaits discovery.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Aug
pubmed:issn
1367-4811
pubmed:author
pubmed:issnType
Electronic
pubmed:day
15
pubmed:volume
25
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
2020-7
pubmed:meshHeading
pubmed:year
2009
pubmed:articleTitle
An investigation into the population abundance distribution of mRNAs, proteins, and metabolites in biological systems.
pubmed:affiliation
Department of Computer Science, Aberystwyth University, Ceredigion SY23 3DB, UK.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't