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Chromosome sorting by flow cytometry can reduce sample complexity and simplify the sequencing of complex genomes by dividing these genomes into smaller parts.
The chapter develops a comprehensive theory of the complexity of induction, which analyzes the inherent difficulty of various kinds of learning problems in terms of sample complexity and computational complexity.
Proteome fractionation with anion exchange chromatography was used to reduce sample complexity and increase quantitative coverage of protein expression.
Coupling immunoaffinity depletion with strong cation exchange (SCX) fractionation further reduces sample complexity, and allowed for the in-depth analysis of the CSF proteomes.
Not only does the omission of this step reduce cost, decrease sample complexity and provide a large time savings over other quantitative proteomic approaches that are competing for clinical acceptance [18], [24], but allows for the detection, identification and quantification of endogenous protein variants in a single analysis.
The largest hindrances to protein identification by mass spectrometry are sample complexity and dynamic range.
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Currently, analysis of pollination drops is done by systems-scale analysis, which poses a number of challenges including sample complexity, dynamic range, and purity (Mallick and Kuster, 2010).
The consortium has adapted a strategy that relies on the purification of individual chromosome arms from wheat telosomic lines [ 2] by flow-cytometric sorting to reduce the sample complexity [ 14] and obtain chromosome-specific genomic data.
In the latter case, we provide both algorithms and sample complexity results for the class of scoring functions, and further validate the approach empirically.
For proteomics, we applied a similar work-flow, whereby chromatographic separation was used to amplify bacterial products via reduction of the sample complexity prior to MS analysis, and construction and interrogation of a smaller custom database (rather than complex databases, ie NCBI or SwissProt) was used for selective analysis of bacterial peptides.
In the case of proteins, the bio-barcode assay can be between one and six orders of magnitude more sensitive than conventional ELISA-based assays, depending on target and sample complexity [40, 41].
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