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Cited by 183

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Thermal denaturation of double-stranded nucleic acids: prediction of temperatures critical for gradient gel electrophoresis and polymerase chain reaction

Open access
Steger, Gerhard·1994·Nucleic Acids Research

Abstract

A program is described which calculates the thermal stability and the denaturation behaviour of double-stranded DNAs and RNAs up to a length of 1000 base pairs. The algorithm is based on recursive generation of conditional and a priori probabilities for base stacking. Output of the program may be compared directly to experimental results; thus the program may be used to optimize the nucleic acid fragments, the primers and the experimental conditions prior to experiments like polymerase chain reactions, temperature-gradient gel electrophoresis, denaturing-gradient gel electrophoresis and hybridizations. The program is available in three versions; the first version runs interactively on VAXstations producing graphics output directly, the second is implemented as part of the HUSAR package at GENIUSnet, the third runs on any computer producing text output which serves as input to available graphics programs.

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Crossref · 10.1093/nar/22.14.2760

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Metadata

Authors
Steger, G.
Venue
Nucleic Acids Research
Published
1994
Volume
22
Issue
14
Pages
2760-2768
ISSN
  • 0305-1048 (ISSN-L)
  • 1362-4962
OpenAlex
W2070484449
Cited by
183
References
2
FWCI
0.98
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Thermal denaturation of double-stranded nucleic acids: prediction of temperatures critical for gradient gel electrophoresis and polymerase chain reaction. https://app.cochat.ai/papers/10.1093/nar/22.14.2760
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Steger, G. (1994). Thermal denaturation of double-stranded nucleic acids: prediction of temperatures critical for gradient gel electrophoresis and polymerase chain reaction. Nucleic Acids Research. https://doi.org/10.1093/nar/22.14.2760

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

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