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All 3 authors maintain private chiropractic practices from where all of the patient files in this study were taken.
Additional CEL files from [ 33] were combined with CEL files in this study, analysed with dChip and expression values imported into Chipster 2.12 [ 76].
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The input signals are usually read from a text file; in this study the same descriptors were used as for MLR modelling.
The log-files in this study were restricted to the main DDs presented above (CP, AP, GE, UTI and PO).
The files used in this study are listed in Additional file 6. ChIP-seq and chromatin state data were analyzed using Seqmonk (http://www.bioinformatics.babraham.ac.uk/projects/seqmonk/).ac.uk/projects/seqmonk/
We conclude that iFBA is a significant improvement over the individual rFBA and ODE modeling paradigms.All MATLAB files used in this study are available at http://www.simtk.org/home/ifba/.Supplementary data are available at Bioinformatics online.
This website also provides links to sample data files used in this study.
We would also like to acknowledge the IVS (Nothnagel et al. 2016) for providing the VEX files used in this study.
The synthetic target speech files used in this study were generated by DECtalk [17], which is a text-to-speech (TTS) system produced by Fonix Corporation that internally uses KLSYN88 as the backend synthesizer.
The CDF files used in this study were essentially derived from "AtTA.cdf".
All files used in this study were downloaded from the National Center for Biotechnology Information (NCBI) website in GenBank format using RefSeq [85] data when available or GenBank [86] otherwise.
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