New Results
SuPreMo: a computational tool for streamlining in silico perturbation using sequence-based predictive models
View ORCID ProfileKetrin Gjoni, View ORCID ProfileKatherine S. Pollard
doi: https://doi.org/10.1101/2023.11.03.565556
Ketrin Gjoni
1Gladstone Institute of Data Science and Biotechnology, San Francisco, CA 94158, USA
2Department of Epidemiology & Biostatistics, University of California, San Francisco, CA 94158, USA
Katherine S. Pollard
1Gladstone Institute of Data Science and Biotechnology, San Francisco, CA 94158, USA
2Department of Epidemiology & Biostatistics, University of California, San Francisco, CA 94158, USA
3Chan Zuckerberg Biohub, San Francisco, CA 94158, USA
Posted November 05, 2023.
SuPreMo: a computational tool for streamlining in silico perturbation using sequence-based predictive models
Ketrin Gjoni, Katherine S. Pollard
bioRxiv 2023.11.03.565556; doi: https://doi.org/10.1101/2023.11.03.565556
Subject Area
Subject Areas
- Biochemistry (13697)
- Bioengineering (10429)
- Bioinformatics (33141)
- Biophysics (17097)
- Cancer Biology (14169)
- Cell Biology (20098)
- Clinical Trials (138)
- Developmental Biology (10866)
- Ecology (16008)
- Epidemiology (2067)
- Evolutionary Biology (20334)
- Genetics (13392)
- Genomics (18629)
- Immunology (13741)
- Microbiology (32149)
- Molecular Biology (13380)
- Neuroscience (70031)
- Paleontology (526)
- Pathology (2188)
- Pharmacology and Toxicology (3741)
- Physiology (5860)
- Plant Biology (12020)
- Synthetic Biology (3365)
- Systems Biology (8163)
- Zoology (1841)