New Results
Single-cell entropy for accurate estimation of differentiation potency from a cell’s transcriptome
Andrew E Teschendorff
doi: https://doi.org/10.1101/084202
Andrew E Teschendorff
1CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, 320 Yue Yang Road, Shanghai 200031, China.
2Department of Women’s Cancer, University College London, 74 Huntley Street, London WC1E 6AU, United Kingdom.
3Statistical Cancer Genomics, Paul O’Gorman Building, UCL Cancer Institute, University College London, 72 Huntley Street, London WC1E 6BT, United Kingdom.
Article usage
Posted October 30, 2016.
Single-cell entropy for accurate estimation of differentiation potency from a cell’s transcriptome
Andrew E Teschendorff
bioRxiv 084202; doi: https://doi.org/10.1101/084202
Subject Area
Subject Areas
- Biochemistry (11730)
- Bioengineering (8743)
- Bioinformatics (29179)
- Biophysics (14964)
- Cancer Biology (12080)
- Cell Biology (17399)
- Clinical Trials (138)
- Developmental Biology (9417)
- Ecology (14174)
- Epidemiology (2067)
- Evolutionary Biology (18294)
- Genetics (12233)
- Genomics (16791)
- Immunology (11858)
- Microbiology (28051)
- Molecular Biology (11575)
- Neuroscience (60919)
- Paleontology (451)
- Pathology (1870)
- Pharmacology and Toxicology (3238)
- Physiology (4955)
- Plant Biology (10422)
- Synthetic Biology (2881)
- Systems Biology (7338)
- Zoology (1650)