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The evolutionary transition from uracil to thymine balances the genetic code
Umeå universitet, Samhällsvetenskapliga fakulteten, Enheten för demografi och åldrandeforskning (CEDAR).ORCID-id: 0000-0001-9188-5518
1996 (Engelska)Ingår i: Journal of Chemometrics, ISSN 0886-9383, E-ISSN 1099-128X, Vol. 10, s. 163-170Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

A multivariate quantitative physicochemical characterization of the five bases adenine (A), cytosine (C), guanine (G), thymine (T) and uracil (U), followed by principal component analysis, shows that the relative dissimilarities between the bases of DNA (A, C, G and T) are almost the same (i.e. balanced). In contrast, mRNA (containing U instead of T) has a considerably larger relative physicochemical similarity between C and U than between all other pairs of bases and is therefore inherently more unbalanced. These results provide a physicochemical explanation of the presence of thymine instead of uracil as an element of DNA. The principal component scores enable a quantitative description of nucleic acid sequence data to be made for structure-activity modelling purposes.

Ort, förlag, år, upplaga, sidor
John Wiley & Sons, 1996. Vol. 10, s. 163-170
Nyckelord [en]
multivariate characterization, DNA, nucleotides
Nationell ämneskategori
Organisk kemi
Identifikatorer
URN: urn:nbn:se:umu:diva-142533DOI: 10.1002/(SICI)1099-128X(199603)10:2<163::AID-CEM415>3.0.CO;2-SOAI: oai:DiVA.org:umu-142533DiVA, id: diva2:1161991
Tillgänglig från: 2017-12-01 Skapad: 2017-12-01 Senast uppdaterad: 2018-06-09
Ingår i avhandling
1. Deciphering sequence data: A multivariate approach
Öppna denna publikation i ny flik eller fönster >>Deciphering sequence data: A multivariate approach
1997 (Engelska)Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
Abstract [en]

In this thesis, attention has been focused on the quantitative description of nucleic acids, proteins and peptides. The strategy was to use multivariate chemometrical methods for improving the understanding of the complex structural codes of these kinds of biological molecules. Tools have been developed that enable quantitative modelling of biological molecules, i.e. models based on data that quantitatively describes their properties. The advantage of such models is that they provide interpretations in terms of chemical characteristics for complex features such as similarity, dissimilarity and potency.

By a multivariate physical-chemical characterization of the building blocks of nucleic acids and proteins, i.e. nucleosides and amino acids, descriptive scales have been developed, so called principal properties. The scales give a description of the intrinsic properties of these building blocks. The multivariate characterization results in a multi-property matrix. A principal component analysis of the multi-property matrix gives a small number of latent variables which are considered as the principal properties of the characterized molecules.

The principal property scales may be used for a wide range of different purposes, such as detecting trends and groupings in large sequence data sets, and for analyzing quantitative relationships between structure and function. In statistical experimental design, the descriptors are well suited as design variables to select combinations of amino acids in such a way that they span a wide range of properties.

The use of these principal property descriptors is demonstrated in the quantitative modelling of relationships between structure and activity of various peptide series, DNA-promoters and in the quantitative modelling of transfer ribonucleic acid sequence data (tRNA).

Ort, förlag, år, upplaga, sidor
Umeå: Solfjädern Offset AB, 1997. s. 76
Nyckelord
Principal properties, amino acids, nucleotides, tRNA, DNA, multivariate data analysis, sequence analysis, QSAR, quantitative sequence activity relationships
Nationell ämneskategori
Organisk kemi
Identifikatorer
urn:nbn:se:umu:diva-142699 (URN)91-7191-337-8 (ISBN)
Disputation
1997-06-06, N320, Naturvetarhuset, 90187, Umeå, 14:00 (Svenska)
Opponent
Handledare
Tillgänglig från: 2023-02-03 Skapad: 2017-12-08 Senast uppdaterad: 2023-02-03Bibliografiskt granskad

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Sandberg Hiltunen, Maria

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Journal of Chemometrics
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