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Record W1605117550 · doi:10.3390/jmse3020382

Transcriptome Survey of a Marine Food Fish: Asian Seabass (Lates calcarifer)

2015· article· en· W1605117550 on OpenAlexaff
Natascha May Thevasagayam, Prakki Sai Rama Sridatta, Junhui Jiang, Amy H.Y. Tong, Jolly M. Saju, Kathiresan Purushothaman, Hsiao Yuen Kwan, Si Yan Ngoh, Woei Chang Liew, Inna S. Kuznetsova, Xueyan Shen, Si Lok, Shubha Vij, László Orbán

Bibliographic record

VenueJournal of Marine Science and Engineering · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIdentification and Quantification in Food
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
FundersNational Research Foundation
KeywordsTranscriptomeBiologyLatesDe novo transcriptome assemblySequence assemblyGenomeBarramundiComputational biologyPyrosequencingDNA sequencingWhole genome sequencingGenome projectGeneticsEvolutionary biologyFisheryGeneFish <Actinopterygii>

Abstract

fetched live from OpenAlex

The Asian seabass (or barramundi; Lates calcarifer) is a marine teleost and a popular food fish in Southeast Asia and Australia. To date, comprehensive genome and transcriptome sequence information has not been available for this species in public repositories. Here, we report a comprehensive de novo transcriptome assembly of the Asian seabass. These data will be useful for the development of molecular tools for use in aquaculture of Asian seabass as well as a resource for genome annotation. The transcriptome was obtained from sequences generated from organs of multiple individuals using three different next-generation sequencing platforms (454-FLX Titanium, SOLiD 3+, and paired-end Illumina HiSeq 2000). The assembled transcriptome contains &gt;80% of the expected protein-coding loci, with 58% of these represented by a predicted full-length cDNA sequence when compared to the available Nile tilapia RefSeq dataset. Detailed descriptions of the various steps involved in sequencing and assembling a transcriptome are provided to serve as a helpful guide for transcriptome projects involving de novo assembly of short sequence reads for non-model teleosts or any species of interest.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.714
Threshold uncertainty score0.266

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.031
GPT teacher head0.257
Teacher spread0.226 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations15
Published2015
Admission routes1
Has abstractyes

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