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Applications and statistics for multiple high-scoring segments in molecular sequences.

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Karlin, S, Altschul, S F·1993·Proceedings of the National Academy of Sciences

Abstract

Score-based measures of molecular-sequence features provide versatile aids for the study of proteins and DNA. They are used by many sequence data base search programs, as well as for identifying distinctive properties of single sequences. For any such measure, it is important to know what can be expected to occur purely by chance. The statistical distribution of high-scoring segments has been described elsewhere. However, molecular sequences will frequently yield several high-scoring segments for which some combined assessment is in order. This paper describes the statistical distribution for the sum of the scores of multiple high-scoring segments and illustrates its application to the identification of possible transmembrane segments and the evaluation of sequence similarity.

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Metadata

Authors
Karlin, S., & Altschul, S. F.
Venue
Proceedings of the National Academy of Sciences
Published
1993-06-15
Volume
90
Issue
12
Pages
5873-5877
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W1965998064
Cited by
367
References
0
FWCI
3.50
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Applications and statistics for multiple high-scoring segments in molecular sequences. https://app.cochat.ai/papers/10.1073/pnas.90.12.5873
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Karlin, S., & Altschul, S. F. (1993). Applications and statistics for multiple high-scoring segments in molecular sequences. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.90.12.5873

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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