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Csardi, Gabor

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Csardi

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Csardi, Gabor

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2012 - 20152

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Author's Publications: search.filters.isAuthorOfPublication.03b36324-3945-4bb7-ba8a-5e394a08546d

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    Accounting for Experimental Noise Reveals That mRNA Levels, Amplified by Post-Transcriptional Processes, Largely Determine Steady-State Protein Levels in Yeast
    (Public Library of Science, 2015) Csardi, Gabor; Franks, Alexander M.; Choi, David S.; Airoldi, Edoardo; Drummond, D. Allan
    Cells respond to their environment by modulating protein levels through mRNA transcription and post-transcriptional control. Modest observed correlations between global steady-state mRNA and protein measurements have been interpreted as evidence that mRNA levels determine roughly 40% of the variation in protein levels, indicating dominant post-transcriptional effects. However, the techniques underlying these conclusions, such as correlation and regression, yield biased results when data are noisy, missing systematically, and collinear---properties of mRNA and protein measurements---which motivated us to revisit this subject. Noise-robust analyses of 24 studies of budding yeast reveal that mRNA levels explain more than 85% of the variation in steady-state protein levels. Protein levels are not proportional to mRNA levels, but rise much more rapidly. Regulation of translation suffices to explain this nonlinear effect, revealing post-transcriptional amplification of, rather than competition with, transcriptional signals. These results substantially revise widely credited models of protein-level regulation, and introduce multiple noise-aware approaches essential for proper analysis of many biological phenomena.
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    ExPASy: SIB bioinformatics resource portal
    (Oxford University Press, 2012) Artimo, Panu; Jonnalagedda, Manohar; Arnold, Konstantin; Baratin, Delphine; Csardi, Gabor; de Castro, Edouard; Duvaud, Séverine; Flegel, Volker; Fortier, Arnaud; Gasteiger, Elisabeth; Grosdidier, Aurélien; Hernandez, Céline; Ioannidis, Vassilios; Kuznetsov, Dmitry; Liechti, Robin; Moretti, Sébastien; Mostaguir, Khaled; Redaschi, Nicole; Rossier, Grégoire; Xenarios, Ioannis; Stockinger, Heinz
    ExPASy (http://www.expasy.org) has worldwide reputation as one of the main bioinformatics resources for proteomics. It has now evolved, becoming an extensible and integrative portal accessing many scientific resources, databases and software tools in different areas of life sciences. Scientists can henceforth access seamlessly a wide range of resources in many different domains, such as proteomics, genomics, phylogeny/evolution, systems biology, population genetics, transcriptomics, etc. The individual resources (databases, web-based and downloadable software tools) are hosted in a ‘decentralized’ way by different groups of the SIB Swiss Institute of Bioinformatics and partner institutions. Specifically, a single web portal provides a common entry point to a wide range of resources developed and operated by different SIB groups and external institutions. The portal features a search function across ‘selected’ resources. Additionally, the availability and usage of resources are monitored. The portal is aimed for both expert users and people who are not familiar with a specific domain in life sciences. The new web interface provides, in particular, visual guidance for newcomers to ExPASy.