GenoML: Automated Machine Learning for Genomics
Not on the map. Why?
Abstract (arXiv)
GenoML is a Python package automating machine learning workflows for genomics (genetics and multi-omics) with an open science philosophy. Genomics data require significant domain expertise to clean, pre-process, harmonize and perform quality control of the data. Furthermore, tuning, validation, and interpretation involve taking into account the biology and possibly the limitations of the underlying data collection, protocols, and technology. GenoML's mission is to bring machine learning for genomics and clinical data to non-experts by developing an easy-to-use tool that automates the full development, evaluation, and deployment process. Emphasis is put on open science to make workflows easily accessible, replicable, and transferable within the scientific community. Source code and documentation is available at https://genoml.com.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 4 of its 13 references that are in the map. First posted on arXiv 4 Mar 2021.
Builds on
4 of 13 references.
References · 4
- 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
- 2016XGBoost: A Scalable Tree Boosting Systemcited by 5,120
- 2018Auto-Keras: An Efficient Neural Architecture Search Systemcited by 169
- 2016Evaluation of a Tree-based Pipeline Optimization Tool for Automating Data Sciencecited by 73
Built on by
Citing papers per year: 2023: 1.
1 paper.