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Record W2031970729 · doi:10.1016/j.jala.2006.10.015

Blotting Pattern Optimization of Contact-Based Microarray Spotting

2007· article· en· W2031970729 on OpenAlexaff
Masatetsu Wake, Peyman Najmabadi, A.A. Goldenberg

Bibliographic record

VenueJALA Journal of the Association for Laboratory Automation · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Biosensing Techniques and Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBlotProteomicsSpottingComputational biologyComputer scienceBiologyGeneArtificial intelligenceGenetics

Abstract

fetched live from OpenAlex

Microarray analysis as a tool that provides the opportunity for simultaneous study of thousands of molecules has greatly contributed to research in many areas including functional genomics and proteomics, disease diagnosis and drug discovery. Pin-based spotting has been widely used in microarray fabrication. This paper investigates blotting procedure, that is, removing excess reagent from pins. A new optimum blotting pattern is proposed. Blotting constraints and parameters are identified and a new pattern, Beta program is proposed and compared with a patented and commonly used blotting pattern, Alpha program. A simulation program has been developed using LabVIEW to demonstrate and compare different blotting patterns. Based on the simulation results, the optimal blotting pattern in terms of speed of blotting operation and density of spots on a slide using different types of source microplates has been obtained. The optimum Beta program showed an increase of 11 times in the density of spots compared to the Alpha program. The Beta program is ready for implemention to improve the efficiency of blotting procedure.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.511
Threshold uncertainty score0.224

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 head0.005
GPT teacher head0.253
Teacher spread0.248 · 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

Citations1
Published2007
Admission routes1
Has abstractyes

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