2/20/2024 0 Comments Western blot analysis definitionprovided on the same measurement scale, is typically limited by the experimental setup, which constitutes a bottleneck for mathematical models with high complexity. Therefore, the number of experiments that are comparable to each other, i.e. Frequently, the generation of these type of data is achieved by techniques like Western blotting, quantitative real-time polymerase chain reaction, reverse phase protein arrays or flow and mass cytometry which only generate measurements on a relative scale. The approach of mathematical modeling to analyse and understand dynamic processes of biological systems requires the collection and quantification of time-resolved experimental data for many different experimental conditions. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Ĭompeting interests: The authors have declared that no competing interests exist. The authors acknowledge support by the Open Access Publication Fund of the University of Freiburg and the state of Baden-Württemberg through bwHPC. 01KU1902A) as well as by the German Research Foundation (DFG) through the grants TRR 179 (Grant No. įunding: This work was supported by the German Ministry of Education and Research (BMBF) through the grants LiSyM (Grant No. The source code of the package is provided at. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.ĭata Availability: All relevant data are within the paper and its Supporting information files. Received: FebruAccepted: JPublished: August 10, 2022Ĭopyright: © 2022 Kemmer et al. An implementation of the method is provided with the R package blotIt including refined ways of visualization.Ĭitation: Kemmer S, Bang S, Rosenblatt M, Timmer J, Kaschek D (2022) BlotIt-Optimal alignment of Western blot and qPCR experiments. Our approach is applicable to all sorts of relative measurements and does not need a particular experimental condition that has been measured over all available scales. In addition, an error model can be specified to adequately weight the different data points and obtain scaling-model based confidence intervals of the finally scaled data points. We propose an alignment model to estimate these scaling factors and provide the possibility to adapt this model depending on the measurement technique of interest. Here, we present a new flexible method to align measurement data that obeys different scaling factors and compare it to existing normalization approaches. In turn, the number of measurements corresponding to the same scale enabling comparability is limited. However, most of the established experimental techniques such as Western blot, or quantitative real-time polymerase chain reaction only provide measurements on a relative scale, since different sample volumes, experimental adjustments or varying development times of a gel lead to systematic shifts in the data. To do so, it is typically important to compare experimental measurements over broad time ranges and various experimental conditions, e.g. In order to infer model parameters and provide a useful model that can be employed for systems understanding and hypothesis testing, the model is often calibrated on quantitative, time-resolved data. Biological systems are frequently analyzed by means of mechanistic mathematical models.
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