Sequence data for 'Machine-driven parameter-space exploration of biochemical reactions'
View DatasetDescription
The development of complex, multi-step omics methods in molecular biology is a laborious, costly, iterative and often intuition-bound process where an optimum is sought in a parameter space through step-by-step optimisations. The the difficulty of miniaturising assays and the cost of the experiments limit the dynamic range and the number of parameters that can be explored. However, because of non-linearities of the response of biochemical systems to their reagent concentrations, a broad dynamic range is necessary. Here we demonstrate the use of a high-performance nanoliter handling platform (Labcyte Echo 525) and computer generation of liquid transfer programs to explore in quadruplicates more than 600 combination of 4 parameters of a biochemical reaction, which lead us to uncover non-linear responses, parameter interactions and novel mechanical insights. With the increased availability of « cloud biology» computer-driven laboratory platforms, our results participate in changing methods development for biotechnology towards reproducible, computer-aided exhaustive characterisation of biochemical systems. This dataset contains the raw sequencing data produced with an Illumina MiSeq instrument for this project. FASTQ files and sample sheets are found in the usual location (Data/Intensities/BaseCalls). The "Thumbnail_Images" and "L001" directories were deleted to save space. Run IDs: 171227_M00528_0321_000000000-B4GLP, 180403_M00528_0348_000000000-B4GP8, 180517_M00528_0364_000000000-BRGK6, 180123_M00528_0325_000000000-B4PCK, 180411_M00528_0351_000000000-BN3BL, 180606_M00528_0367_000000000-BN3FG, 180326_M00528_0346_000000000-B4GJR, 180501_M00528_0359_000000000-B4PJY, 180607_M00528_0368_000000000-BN9KM
Citations (2)
Cited on 01 January 2026
Weight: 1.00
Cited on 06 February 2020
Weight: 1.36
Mentions (1)
- https://github.com/oist/labcyte-rt-optimisationSoftware Heritage
Mentioned on 17 May 2024
Weight: 1.64
Metrics Over Time
Publication Details
Subfield
Molecular Biology
Field
Biochemistry, Genetics and Molecular Biology
Domain
Life Sciences
Confidence Score
95%
Source
Open Alex