New Results
MetaRNN: Differentiating Rare Pathogenic and Rare Benign Missense SNVs and InDels Using Deep Learning
Chang Li, Degui Zhi, Kai Wang, View ORCID ProfileXiaoming Liu
doi: https://doi.org/10.1101/2021.04.09.438706
Chang Li
1USF Genomics & College of Public Health, University of South Florida, Tampa, FL, USA
Degui Zhi
2School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA
Kai Wang
3Children’s Hospital of Philadelphia & Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
Xiaoming Liu
1USF Genomics & College of Public Health, University of South Florida, Tampa, FL, USA
Posted April 11, 2021.
MetaRNN: Differentiating Rare Pathogenic and Rare Benign Missense SNVs and InDels Using Deep Learning
Chang Li, Degui Zhi, Kai Wang, Xiaoming Liu
bioRxiv 2021.04.09.438706; doi: https://doi.org/10.1101/2021.04.09.438706
Subject Area
Subject Areas
- Biochemistry (11752)
- Bioengineering (8752)
- Bioinformatics (29200)
- Biophysics (14974)
- Cancer Biology (12096)
- Cell Biology (17411)
- Clinical Trials (138)
- Developmental Biology (9421)
- Ecology (14182)
- Epidemiology (2067)
- Evolutionary Biology (18308)
- Genetics (12245)
- Genomics (16803)
- Immunology (11869)
- Microbiology (28097)
- Molecular Biology (11594)
- Neuroscience (60969)
- Paleontology (451)
- Pathology (1871)
- Pharmacology and Toxicology (3238)
- Physiology (4959)
- Plant Biology (10427)
- Synthetic Biology (2886)
- Systems Biology (7340)
- Zoology (1651)