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Michael Podvinec

Researcher at University of Basel

Publications -  29
Citations -  1925

Michael Podvinec is an academic researcher from University of Basel. The author has contributed to research in topics: Pregnane X receptor & Constitutive androstane receptor. The author has an hindex of 19, co-authored 29 publications receiving 1825 citations. Previous affiliations of Michael Podvinec include Swiss Institute of Bioinformatics & Rutgers University.

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The estrogen-related receptor α (ERRα) functions in PPARγ coactivator 1α (PGC-1α)-induced mitochondrial biogenesis

TL;DR: This paper showed that ERRα is an effector of the transcriptional coactivator PGC-1α and that it regulates the expression of genes involved in oxidative phosphorylation and mitochondrial biogenesis.
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NUBIScan, an in silico approach for prediction of nuclear receptor response elements.

TL;DR: NUBIScan, a computer algorithm to predict DNA recognition sites for NRs in the regulatory regions of genes, provides more specific identification of functional sites than previous in silico approaches, and consistently identified new functional NR binding sites in sets of large sequences, which had eluded previous analyses.
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The Protein Model Portal.

TL;DR: The goal of the Protein Model Portal (PMP) is to provide a single portal which gives access to the various models that can be leveraged from PSI targets and other experimental protein structures.
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CXR, a chicken xenobiotic-sensing orphan nuclear receptor, is related to both mammalian pregnane X receptor (PXR) and constitutive androstane receptor (CAR)

TL;DR: Results provide convincing evidence for a major role of CXR in the regulation of CYP2H1 and add a member to the family of xenobiotic-activated orphan nuclear receptors to regulate drug-mediated induction of cytochromes P450 (CYP).
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The protein structure initiative structural genomics knowledgebase

TL;DR: The Protein Structure Initiative Structural Genomics Knowledgebase (PSI SGKB) as mentioned in this paper was created to turn the products of the PSI structural genomics effort into knowledge that can be used by the biological research community to understand living systems and disease.