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Record W2514633836 · doi:10.1016/j.dib.2016.07.035

Global proteomics dataset of miR-126 overexpression in acute myeloid leukemia

2016· article· en· W2514633836 on OpenAlexafffund
Erwin M. Schoof, Eric R. Lechman, John E. Dick

Bibliographic record

VenueData in Brief · 2016
Typearticle
Languageen
FieldChemistry
TopicAdvanced Proteomics Techniques and Applications
Canadian institutionsUniversity Health NetworkPrincess Margaret Cancer CentreUniversity of Toronto
FundersCanadian Institutes of Health ResearchTerry Fox FoundationEuropean CommissionCanadian Cancer SocietyOntario Ministry of Health and Long-Term CareOntario Genomics InstituteEuropean Molecular Biology Organization
KeywordsMyeloid leukemiaProteomicsHaematopoiesismicroRNAComputational biologyIdentifierLeukemiaBiologyStem cellBioinformaticsCancer researchComputer scienceCell biologyImmunologyGeneticsGene

Abstract

fetched live from OpenAlex

A deep proteomics analysis was conducted on a primary acute myeloid leukemia culture system to identify potential protein targets regulated by miR-126. Leukemia cells were transduced either with an empty control lentivirus or one containing the sequence for miR-126, and resulting cells were analyzed using ultra-high performance liquid chromatography (UHPLC) coupled with high resolution mass spectrometry. The mass spectrometry data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PRIDE: PXD001994. The proteomics data and statistical analysis described in this article is associated with a research article, "miR-126 regulates distinct self-renewal outcomes in normal and malignant hematopoietic stem cells" (Lechman et al., 2016) [1], and serves as a resource for researchers working in the field of microRNAs and their regulation of protein levels.

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)0.000
metaresearch head score (Gemma)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.322
Threshold uncertainty score0.409

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0010.001
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 head0.021
GPT teacher head0.312
Teacher spread0.292 · 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

Citations11
Published2016
Admission routes2
Has abstractyes

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