Biological Sequence Analysis¶
Durbin, R., Eddy, S. R., Krogh, A., & Mitchison, G. (1998). Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids. Cambridge University Press.
Cited by¶
1 citation across 1 artifact.
Each citation links to the sentence it supports in the citing article.
Primes¶
- Parsing
- In bioinformatics a DNA sequence is parsed into reading frames, exons, introns, and binding sites using grammar-like apparatus, recovering a gene model that was never visible in the bare sequence.
This sourceFoundational application of stochastic context-free grammars and HMMs to parse DNA/RNA into genes, reading frames, and structure.
Supported in partVerified against the publisher's abstract
The abstract confirms grammar-based probabilistic models and HMMs applied to biological sequences, but names RNA secondary structure only — not reading frames, exons, introns, or gene models.
“hidden Markov models are used for analysing biological sequences, linguistic-grammar-based probabilistic models for identifying RNA secondary structure”
- In bioinformatics a DNA sequence is parsed into reading frames, exons, introns, and binding sites using grammar-like apparatus, recovering a gene model that was never visible in the bare sequence.
Verification¶
Does it exist? Confirmed. This work's DOI resolves to a registered record, which fixes its identity. That is all it fixes.
Does it back the claim? Read against the text for 1 of 1 citation: 1 supported in part. Each verdict is shown under its citation below, with what in the work backs the sentence.
Support is checked per citation rather than per work — the same source can be cited soundly in one article and wrongly in another. Per-citation recording began recently, so a citation with no recorded check is a gap in the record rather than evidence it went unchecked.
See how references were verified.
Registry ID ref:702e02761ff9 · see in the full table