Linked Life Data

20365196

Source:http://linkedlifedata.com/resource/pubmed/id/20365196

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
6 Pt 1
pubmed:dateCreated
2010-4-6
pubmed:abstractText
Sequence alignment is a tool in bioinformatics that is used to find homological relationships in large molecular databases. It can be mapped on the physical model of directed polymers in random media. We consider the finite-temperature version of local sequence alignment for proteins and study the transition between the linear phase and the biologically relevant logarithmic phase, where the free energy grows linearly or logarithmically with the sequence length. By means of numerical simulations and finite-size-scaling analysis, we determine the phase diagram in the plane that is spanned by the gap costs and the temperature. We use the most frequently used parameter set for protein alignment. The critical exponents that describe the parameter-driven transition are found to be explicitly temperature dependent. Furthermore, we study the shape of the (free-) energy distribution close to the transition by rare-event simulations down to probabilities on the order 10(-64). It is well known that in the logarithmic region, the optimal score distribution (T=0) is described by a modified Gumbel distribution. We confirm that this also applies for the free-energy distribution (T>0). However, in the linear phase, the distribution crosses over to a modified Gaussian distribution.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Dec
pubmed:issn
1550-2376
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
80
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
061913
pubmed:meshHeading
pubmed:year
2009
pubmed:articleTitle
Finite-temperature local protein sequence alignment: percolation and free-energy distribution.
pubmed:affiliation
Department of Applied Mathematics, Université Paris Descartes, 45 rue des Saint-Pères, F-75270 Paris Cedex 06, France.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't