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Record W1869957243 · doi:10.1186/1471-2105-6-183

Inconsistencies over time in 5% of NetAffx probe-to-gene annotations

2005· letter· en· W1869957243 on OpenAlexaff
Carolina Perez‐Iratxeta, Miguel A. Andrade‐Navarro

Bibliographic record

VenueBMC Bioinformatics · 2005
Typeletter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGene expression and cancer classification
Canadian institutionsOntario Genomics
FundersMinistry of Education, India
KeywordsDNA microarrayMicroarrayMicroarray databasesAnnotationMicroarray analysis techniquesComputational biologyBiologyGeneGene AnnotationGeneticsSet (abstract data type)GenomeBioinformaticsComputer scienceGene expression

Abstract

fetched live from OpenAlex

BACKGROUND: DNA microarray probes are designed to match particular mRNA transcripts, often based on expressed sequences like ESTs, or cDNAs, many times incomplete. As a result, the relations between probes and genes can change as the sequence data are updated. However, it is frequent that the reported results of microarray analyses are given just as lists of genes without any reference to the underlying probes. RESULTS: We show for a particular commercial microarray design that the number of probes associated to some genes change with time. These changes concern approximately 5% of the probe sets across the history of annotation releases over a two year span. CONCLUSION: We recommend to report probe set identifiers when publishing microarray results, and to submit those analyses to microarray public databases to ensure that the interpretation of the data is updated with the latest set of annotations.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.028
metaresearch head score (Gemma)0.081
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.028
Threshold uncertainty score0.148

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0280.081
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0020.002
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0050.004

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 head0.016
GPT teacher head0.250
Teacher spread0.234 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations27
Published2005
Admission routes1
Has abstractyes

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