GenoML: Automated Machine Learning for Genomics

no code implementations • 4 Mar 2021 • Mary B. Makarious, Hampton L. Leonard, Dan Vitale, Hirotaka Iwaki, David Saffo, Lana Sargent, Anant Dadu, Eduardo Salmerón Castaño, John F. Carter, Melina Maleknia, Juan A. Botia, Cornelis Blauwendraat, Roy H. Campbell, Sayed Hadi Hashemi, Andrew B. Singleton, Mike A. Nalls, Faraz Faghri

GenoML is a Python package automating machine learning workflows for genomics (genetics and multi-omics) with an open science philosophy.

BIG-bench Machine Learning Philosophy

Learning the progression and clinical subtypes of Alzheimer's disease from longitudinal clinical data

no code implementations • 3 Dec 2018 • Vipul Satone, Rachneet Kaur, Faraz Faghri, Mike A. Nalls, Andrew B Singleton, Roy H. Campbell

The proposed work will enable early detection and characterization of distinct disease subtypes based on clinical heterogeneity.

BIG-bench Machine Learning

Toward Scalable Machine Learning and Data Mining: the Bioinformatics Case

no code implementations • 29 Sep 2017 • Faraz Faghri, Sayed Hadi Hashemi, Mohammad Babaeizadeh, Mike A. Nalls, Saurabh Sinha, Roy H. Campbell

In an effort to overcome the data deluge in computational biology and bioinformatics and to facilitate bioinformatics research in the era of big data, we identify some of the most influential algorithms that have been widely used in the bioinformatics community.

BIG-bench Machine Learning Clustering +3