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The cell rejuvenation atlas: leveraging network biology to identify master regulators of rejuvenation strategies
Research Paper Volume 16, Issue 17 pp 12168—12190 1 Computational Biology Group, CIC bioGUNE-BRTA (Basque Research and Technology Alliance), Bizkaia Technology Park, Derio, Spain 2 Computational Biology Group, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette L-4362, Luxembourg 3 Biomedical Data Science Group, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette L-4362, Luxembourg 4 Ikerbasque, Basque...
The cell rejuvenation atlas: leveraging network biology to identify master regulators of rejuvenation strategies
Research Paper Volume 16, Issue 17 pp 12168—12190 1 Computational Biology Group, CIC bioGUNE-BRTA (Basque Research and Technology Alliance), Bizkaia Technology Park, Derio, Spain 2 Computational Biology Group, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette L-4362, Luxembourg 3 Biomedical Data Science Group, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette L-4362, Luxembourg 4 Ikerbasque, Basque...
SinCMat: A single-cell-based method for predicting functional maturation transcription factors
Highlights • SinCMat is the first computational method for identifying functional maturation TFs • SinCMat predicted known and novel maturation TFs • SinCMat is applicable to any mouse or human cell type • SinCMat is embedded in a user-friendly web interface Summary A major goal of regenerative medicine is to generate tissue-specific mature and functional cells. However, current cell engineering protocols are still unable to systematically produce fully mature functional cells.
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