ArticleComputers & chemical engineering2014
Modeling and Global Optimization of DNA separation.
Article in Computers & chemical engineering, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
2 citing papers in PubMed, 4 citations in OpenAlex.
- Long-Read, High-Resolution Sanger Sequencing by Micelle-Tagging Electrophoresis.Electrophoresis · 2026Article
- Optimization of ELFSE DNA sequencing with EOF counterflow and microfluidics.Electrophoresis · 2014Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
We develop a non-convex non-linear programming problem that determines the minimum run time to resolve different lengths of DNA using a gel-free micelle end-labeled free solution electrophoresis separation method. Our optimization framework allows for efficient determination of the utility of different DNA separation platforms and enables the identification of the optimal operating conditions for these DNA separation devices. The non-linear programming problem requires a model for signal spacing and signal width, which is known for many DNA separation methods. As a case study, we show how our approach is used to determine the optimal run conditions for micelle end-labeled free-solution electrophoresis and examine the trade-offs between a single capillary system and a parallel capillary system. Parallel capillaries are shown to only be beneficial for DNA lengths above 230 bases using a polydisperse micelle end-label otherwise single capillaries produce faster separations.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.