Publications by authors named "Michael Dausmann"
Article Synopsis
- * By integrating various datasets, including drug response and gene essentiality screens, researchers identified thousands of protein biomarkers linked to cancer vulnerabilities, many of which were undetectable at the transcript level.
- * The study demonstrates that the predictive power of the proteome for drug response is similarly effective as that of the transcriptome, and even reducing the number of analyzed proteins to 1,500 does not significantly affect this predictive capability.
Motivation: The output of electrospray ionization-liquid chromatography mass spectrometry (ESI-LC-MS) is influenced by multiple sources of noise and major contributors can be broadly categorized as baseline, random and chemical noise. Noise has a negative impact on the identification and quantification of peptides, which influences the reliability and reproducibility of MS-based proteomics data. Most attempts at denoising have been made on either spectra or chromatograms independently, thus, important 2D information is lost because the mass-to-charge ratio and retention time dimensions are not considered jointly.
View Article and Find Full Text PDFReproducible research is the bedrock of experimental science. To enable the deployment of large-scale proteomics, we assess the reproducibility of mass spectrometry (MS) over time and across instruments and develop computational methods for improving quantitative accuracy. We perform 1560 data independent acquisition (DIA)-MS runs of eight samples containing known proportions of ovarian and prostate cancer tissue and yeast, or control HEK293T cells.
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