CodingQuarry: highly accurate hidden Markov model gene prediction in fungal genomes using RNA-seq transcripts

Research article (BMC Genomics, 2015) · cited 248× · AI/ML
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CodingQuarry: highly accurate hidden Markov model gene prediction in fungal genomes using RNA-seq transcripts

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CodingQuarry: highly accurate hidden Markov model gene prediction in fungal genomes using RNA-seq transcripts is a scholarly article[1].

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  • CodingQuarry: highly accurate hidden Markov model gene prediction in fungal genomes using RNA-seq transcripts's instance of is recorded as scholarly article[2].

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APA 4ort.xyz Knowledge Graph. (2026). CodingQuarry: highly accurate hidden Markov model gene prediction in fungal genomes using RNA-seq transcripts. Retrieved May 24, 2026, from https://4ort.xyz/entity/codingquarry-highly-accurate-hidden-markov-model-gene-prediction-in-fungal-genomes-using-rna-seq-transcripts
MLA “CodingQuarry: highly accurate hidden Markov model gene prediction in fungal genomes using RNA-seq transcripts.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/codingquarry-highly-accurate-hidden-markov-model-gene-prediction-in-fungal-genomes-using-rna-seq-transcripts.
BibTeX @misc{4ortxyz_codingquarry-highly-accurate-hidden-markov-model-gene-prediction-in-fungal-genomes-using-rna-seq-transcripts_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{CodingQuarry: highly accurate hidden Markov model gene prediction in fungal genomes using RNA-seq transcripts}}, year = {2026}, url = {https://4ort.xyz/entity/codingquarry-highly-accurate-hidden-markov-model-gene-prediction-in-fungal-genomes-using-rna-seq-transcripts}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): CodingQuarry: highly accurate hidden Markov model gene prediction in fungal genomes using RNA-seq transcripts — https://4ort.xyz/entity/codingquarry-highly-accurate-hidden-markov-model-gene-prediction-in-fungal-genomes-using-rna-seq-transcripts (retrieved 2026-05-24)

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