Iterative method for improved protein structural motif recognition

Bonnie Berger; Mona Singh

doi:10.1145/267521.267527

Iterative method for improved protein structural motif recognition

Bonnie Berger, Mona Singh

Research output: Contribution to conference › Paper › peer-review

3 Scopus citations

Abstract

We present an iterative algorithm that uses randomness and statistical techniques to improve existing methods for recognizing protein structural motifs. Our algorithm is particularly effective in situations where large numbers of sufficiently diverse examples of the motif are not known. These are precisely the situations that pose significant difficulties for previously known methods. We have implemented our algorithm and we demonstrate its performance on the coiled coil motif. We test our program LearnCoil on the domain of 3-stranded coiled coils and subclasses of 2-stranded coiled coils. We show empirically that for these motifs, our method overcomes the problem of limited data.

Original language	English (US)
Pages	37-46
Number of pages	10
DOIs	https://doi.org/10.1145/267521.267527
State	Published - 1997
Externally published	Yes
Event	Proceedings of the 1997 1st Annual International Conference on Computational Molecular Biology, RECOMB - Santa Fe, NM, USA Duration: Jan 20 1997 → Jan 23 1997

Other

Other	Proceedings of the 1997 1st Annual International Conference on Computational Molecular Biology, RECOMB
City	Santa Fe, NM, USA
Period	1/20/97 → 1/23/97

All Science Journal Classification (ASJC) codes

General Engineering

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10.1145/267521.267527

Cite this

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title = "Iterative method for improved protein structural motif recognition",

abstract = "We present an iterative algorithm that uses randomness and statistical techniques to improve existing methods for recognizing protein structural motifs. Our algorithm is particularly effective in situations where large numbers of sufficiently diverse examples of the motif are not known. These are precisely the situations that pose significant difficulties for previously known methods. We have implemented our algorithm and we demonstrate its performance on the coiled coil motif. We test our program LearnCoil on the domain of 3-stranded coiled coils and subclasses of 2-stranded coiled coils. We show empirically that for these motifs, our method overcomes the problem of limited data.",

author = "Bonnie Berger and Mona Singh",

year = "1997",

doi = "10.1145/267521.267527",

language = "English (US)",

pages = "37--46",

note = "Proceedings of the 1997 1st Annual International Conference on Computational Molecular Biology, RECOMB ; Conference date: 20-01-1997 Through 23-01-1997",

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AU - Berger, Bonnie

AU - Singh, Mona

PY - 1997

Y1 - 1997

N2 - We present an iterative algorithm that uses randomness and statistical techniques to improve existing methods for recognizing protein structural motifs. Our algorithm is particularly effective in situations where large numbers of sufficiently diverse examples of the motif are not known. These are precisely the situations that pose significant difficulties for previously known methods. We have implemented our algorithm and we demonstrate its performance on the coiled coil motif. We test our program LearnCoil on the domain of 3-stranded coiled coils and subclasses of 2-stranded coiled coils. We show empirically that for these motifs, our method overcomes the problem of limited data.

AB - We present an iterative algorithm that uses randomness and statistical techniques to improve existing methods for recognizing protein structural motifs. Our algorithm is particularly effective in situations where large numbers of sufficiently diverse examples of the motif are not known. These are precisely the situations that pose significant difficulties for previously known methods. We have implemented our algorithm and we demonstrate its performance on the coiled coil motif. We test our program LearnCoil on the domain of 3-stranded coiled coils and subclasses of 2-stranded coiled coils. We show empirically that for these motifs, our method overcomes the problem of limited data.

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DO - 10.1145/267521.267527

M3 - Paper

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SP - 37

EP - 46

T2 - Proceedings of the 1997 1st Annual International Conference on Computational Molecular Biology, RECOMB

Y2 - 20 January 1997 through 23 January 1997

ER -

Iterative method for improved protein structural motif recognition

Abstract

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