2001Unpublished venueRequires access

Confidence Measures for Fold Recognition.

I. Sommer, Niklas von Öhsen, Alexander Zien, Ralf Zimmer, Thomas Lengauer

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Abstract

Introduction It is a standard procedure to compare new amino acid sequences to databases of proteins that have been studied already in order to find similarities in structure and function. This comparison can be sequence--sequence or sequence-- structure based. In order to compare, an alignment is performed of the target protein sequence (whose structure we are searching) with a template protein (whose structure we know). For a sequence--sequence alignment, the alignment algorithm optimizes a certain scoring function that quantifies the similarities of the amino acids at individual positions. For a sequence--structure alignment, also known as threading, usually the scoring function that is optimized is designed to capture the essence of structural similarity among proteins. These scores are supposed to be comparable between different proteins, since we want to select the template which achieves the highest alignment score to the target protein as our candidate for the structural

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Introduction It is a standard procedure to compare new amino acid sequences to databases of proteins that have been studied already in order to find similarities in structure and function. This comparison can be sequence--sequence or sequence-- structure based. In order to compare, an alignment is performed of the target protein sequence (whose structure we are searching) with a template protein (whose structure we know). For a sequence--sequence alignment, the alignment algorithm optimizes a certain scoring function that quantifies the similarities of the amino acids at individual positions. For a sequence--structure alignment, also known as threading, usually the scoring function that is optimized is designed to capture the essence of structural similarity among proteins. These scores are supposed to be comparable between different proteins, since we want to select the template which achieves the highest alignment score to the target protein as our candidate for the structural

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Available abstract

Introduction It is a standard procedure to compare new amino acid sequences to databases of proteins that have been studied already in order to find similarities in structure and function. This comparison can be sequence--sequence or sequence-- structure based. In order to compare, an alignment is performed of the target protein sequence (whose structure we are searching) with a template protein (whose structure we know). For a sequence--sequence alignment, the alignment algorithm optimizes a certain scoring function that quantifies the similarities of the amino acids at individual positions. For a sequence--structure alignment, also known as threading, usually the scoring function that is optimized is designed to capture the essence of structural similarity among proteins. These scores are supposed to be comparable between different proteins, since we want to select the template which achieves the highest alignment score to the target protein as our candidate for the structural

Key concepts: Threading (protein sequence), Structural alignment, Multiple sequence alignment, Alignment-free sequence analysis, Sequence alignment, Computer science, Sequence (biology), Protein structure prediction

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