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A guide to selecting high-performing antibodies for ADNP (UniProt ID: Q9H2P0) for use in western blot, immunoprecipitation, and immunofluorescence

2024· preprint· en· W4405643069 on OpenAlexafffund
Vera Ruíz Moleón, Charles Alende, Maryam Fotouhi, Riham Ayoubi, Sara González Bolívar, Carl Laflamme

Bibliographic record

VenueF1000Research · 2024
Typepreprint
Languageen
FieldMedicine
TopicMonoclonal and Polyclonal Antibodies Research
Canadian institutionsMontreal Neurological Institute and Hospital
FundersGenentechGovernment of CanadaOntario Genomics InstituteEuropean Federation of Pharmaceutical Industries and AssociationsMerck KGaAMitacsOntario GenomicsGenome CanadaSimons Foundation Autism Research InitiativeBayerPfizerBristol-Myers Squibb
KeywordsWestern blotAntibodyImmunoprecipitationImmunofluorescenceChromatin immunoprecipitationBiologyUniProtComputational biologyMolecular biologyImmunologyGeneGeneticsGene expression

Abstract

fetched live from OpenAlex

ADNP is a multifunctional protein involved in chromatin remodeling, transcription, and microtubule interaction, playing a critical role in brain development, with mutations linked to ADNP -Related Disorder. Here we have characterized seven ADNP commercial antibodies for western blot, immunoprecipitation, and immunofluorescence using a standardized experimental protocol based on comparing read-outs in knockout cell lines and isogenic parental controls. These studies are part of a larger, collaborative initiative seeking to address antibody reproducibility issues by characterizing commercially available antibodies for human proteins and publishing the results openly as a resource for the scientific community. While use of antibodies and protocols vary between laboratories, we encourage readers to use this report as a guide to select the most appropriate antibodies for their specific needs.

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)0.005
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.159
Threshold uncertainty score0.530

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.011
Meta-epidemiology (narrow)0.0040.006
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0080.005
Science and technology studies0.0020.001
Scholarly communication0.0030.003
Open science0.0060.002
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.1590.244

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 head0.063
GPT teacher head0.411
Teacher spread0.347 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations0
Published2024
Admission routes2
Has abstractyes

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