Fatgraph models of proteins

R. C. Penner; Michael Knudsen; Carsten Wiuf; Jørgen Ellegaard Andersen

doi:10.1002/cpa.20340

Fatgraph models of proteins

R. C. Penner^*, Michael Knudsen, Carsten Wiuf, Jørgen Ellegaard Andersen

^*Corresponding author for this work

33 Citations (Scopus)

Abstract

We introduce a new model of proteins that extends and enhances the traditional graphical representation by associating a combinatorial object called a fatgraph to any protein based upon its intrinsic geometry. Fatgraphs can easily be stored and manipulated as triples of permutations, and these methods are therefore amenable to fast computer implementation. Applications include the refinement of structural protein classifications and the prediction of geometric and other properties of proteins from their chemical structures.

Original language	English
Journal	Communications on Pure and Applied Mathematics
Volume	63
Issue number	10
Pages (from-to)	1249-1297
Number of pages	49
ISSN	0010-3640
DOIs	https://doi.org/10.1002/cpa.20340
Publication status	Published - 1 Oct 2010
Externally published	Yes

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10.1002/cpa.20340

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title = "Fatgraph models of proteins",

abstract = "We introduce a new model of proteins that extends and enhances the traditional graphical representation by associating a combinatorial object called a fatgraph to any protein based upon its intrinsic geometry. Fatgraphs can easily be stored and manipulated as triples of permutations, and these methods are therefore amenable to fast computer implementation. Applications include the refinement of structural protein classifications and the prediction of geometric and other properties of proteins from their chemical structures.",

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AU - Wiuf, Carsten

AU - Andersen, Jørgen Ellegaard

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N2 - We introduce a new model of proteins that extends and enhances the traditional graphical representation by associating a combinatorial object called a fatgraph to any protein based upon its intrinsic geometry. Fatgraphs can easily be stored and manipulated as triples of permutations, and these methods are therefore amenable to fast computer implementation. Applications include the refinement of structural protein classifications and the prediction of geometric and other properties of proteins from their chemical structures.

AB - We introduce a new model of proteins that extends and enhances the traditional graphical representation by associating a combinatorial object called a fatgraph to any protein based upon its intrinsic geometry. Fatgraphs can easily be stored and manipulated as triples of permutations, and these methods are therefore amenable to fast computer implementation. Applications include the refinement of structural protein classifications and the prediction of geometric and other properties of proteins from their chemical structures.

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Fatgraph models of proteins

Abstract

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