M
Michaela Fellner
Researcher at Research Institute of Molecular Pathology
Publications - 21
Citations - 3619
Michaela Fellner is an academic researcher from Research Institute of Molecular Pathology. The author has contributed to research in topics: Gene & Biology. The author has an hindex of 8, co-authored 12 publications receiving 3124 citations. Previous affiliations of Michaela Fellner include Austrian Academy of Sciences.
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Journal ArticleDOI
A genome-wide transgenic RNAi library for conditional gene inactivation in Drosophila
Georg Dietzl,Doris Chen,Frank Schnorrer,Kuan-Chung Su,Yulia Barinova,Michaela Fellner,Michaela Fellner,Beate Gasser,Kaolin Kinsey,Kaolin Kinsey,Silvia Oppel,Silvia Oppel,Susanne Scheiblauer,Africa Couto,Vincent Marra,Krystyna Keleman,Krystyna Keleman,Barry J. Dickson,Barry J. Dickson +18 more
TL;DR: The generation and validation of a genome-wide library of Drosophila melanogaster RNAi transgenes, enabling the conditional inactivation of gene function in specific tissues of the intact organism and opening up the prospect of systematically analysing gene functions in any tissue and at any stage of the Drosophile lifespan.
Journal ArticleDOI
Systematic genetic analysis of muscle morphogenesis and function in Drosophila
Frank Schnorrer,Cornelia Schönbauer,Christoph C. H. Langer,Georg Dietzl,Maria Novatchkova,Katharina Schernhuber,Michaela Fellner,Anna Azaryan,Martin Radolf,Alexander Stark,Krystyna Keleman,Barry J. Dickson +11 more
TL;DR: A role in muscle is identified for 2,785 genes, many of which are phylogenetically conserved, including genes implicated in mammalian sarcomere organization and human muscle diseases.
Journal ArticleDOI
The histone chaperone CAF-1 safeguards somatic cell identity
Sihem Cheloufi,Sihem Cheloufi,Ulrich Elling,Barbara Hopfgartner,Youngsook L. Jung,Youngsook L. Jung,Jernej Murn,Jernej Murn,Maria Ninova,Maria Hubmann,Aimee I. Badeaux,Aimee I. Badeaux,Cheen Euong Ang,Danielle Tenen,Danielle Tenen,Daniel J. Wesche,Daniel J. Wesche,Nadezhda Abazova,Nadezhda Abazova,Max Hogue,Max Hogue,Nilgun Tasdemir,Justin Brumbaugh,Justin Brumbaugh,Philipp Rathert,Julian Jude,Francesco Ferrari,Francesco Ferrari,Andres Blanco,Andres Blanco,Michaela Fellner,Daniel Wenzel,Marietta Zinner,Simon E. Vidal,Oliver Bell,Matthias Stadtfeld,Howard Y. Chang,Howard Y. Chang,Geneviève Almouzni,Scott W. Lowe,Scott W. Lowe,John L. Rinn,John L. Rinn,Marius Wernig,Alexei A. Aravin,Yang Shi,Yang Shi,Peter J. Park,Peter J. Park,Josef M. Penninger,Johannes Zuber,Konrad Hochedlinger,Konrad Hochedlinger +52 more
TL;DR: The findings reveal the histone chaperone CAF-1 to be a novel regulator of somatic cell identity during transcription-factor-induced cell-fate transitions and provide a potential strategy to modulate cellular plasticity in a regenerative setting.
Journal ArticleDOI
Rational discovery of molecular glue degraders via scalable chemical profiling
Cristina Mayor-Ruiz,Sophie Bauer,Matthias Brand,Zuzanna Kozicka,Zuzanna Kozicka,Marton Siklos,Hana Imrichova,Ines H. Kaltheuner,Elisa Hahn,Kristina Seiler,Anna Koren,Georg Petzold,Michaela Fellner,Christoph Bock,Christoph Bock,André C. Müller,Johannes Zuber,Matthias Geyer,Nicolas H. Thomä,Stefan Kubicek,Georg E. Winter +20 more
TL;DR: A scalable strategy toward glue degrader discovery is described that is based on chemical screening in hyponeddylated cells coupled to a multi-omics target deconvolution campaign to identify compounds that induce ubiquitination and degradation of cyclin K by prompting an interaction of CDK12–cyclin K with a CRL4B ligase complex.
Journal ArticleDOI
Multilayered VBC score predicts sgRNAs that efficiently generate loss-of-function alleles
Georg Michlits,Julian Jude,Matthias Hinterndorfer,Melanie Talata De Almeida,Gintautas Vainorius,Maria Hubmann,Tobias Neumann,Alexander Schleiffer,Alexander Schleiffer,Thomas R Burkard,Thomas R Burkard,Michaela Fellner,Max Gijsbertsen,Anna K. Traunbauer,Johannes Zuber,Johannes Zuber,Ulrich Elling +16 more
TL;DR: Using optimized screening workflows, the Vienna Bioactivity CRISPR (VBC) scoring system provides an improved selection for sgRNAs that generate loss-of-function alleles, and outperforms previous prediction tools and enables the selection of sg RNAs that effectively produce loss- of- function alleles.