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Cited by 460

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Identifying protein-binding sites from unaligned DNA fragments.

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Stormo, G D, Hartzell, G W·1989·Proceedings of the National Academy of Sciences

Abstract

The ability to determine important features within DNA sequences from the sequences alone is becoming essential as large-scale sequencing projects are being undertaken. We present a method that can be applied to the problem of identifying the recognition pattern for a DNA-binding protein given only a collection of sequenced DNA fragments, each known to contain somewhere within it a binding site for that protein. Information about the position or orientation of the binding sites within those fragments is not needed. The method compares the "information content" of a large number of possible binding site alignments to arrive at a matrix representation of the binding site pattern. The specificity of the protein is represented as a matrix, rather than a consensus sequence, allowing patterns that are typical of regulatory protein-binding sites to be identified. The reliability of the method improves as the number of sequences increases, but the time required increases only linearly with the number of sequences. An example, using known cAMP receptor protein-binding sites, illustrates the method.

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Metadata

Authors
Stormo, G. D., & Hartzell, G. W.
Venue
Proceedings of the National Academy of Sciences
Published
1989-02
Volume
86
Issue
4
Pages
1183-1187
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W1975924111
Cited by
460
References
0
FWCI
2.60
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Identifying protein-binding sites from unaligned DNA fragments. https://app.cochat.ai/papers/10.1073/pnas.86.4.1183
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Stormo, G. D., & Hartzell, G. W. (1989). Identifying protein-binding sites from unaligned DNA fragments. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.86.4.1183

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.