Machine Learning for Integrating Data in Biology and Medicine:
Principles, Practice, and Opportunities

Machine Learning for Integrating Data in Biology and Medicine: Principles, Practice, and Opportunities

30 June 2018

Anna Goldenberg

Michael M. Hoffman

Papers citing "Machine Learning for Integrating Data in Biology and Medicine: Principles, Practice, and Opportunities"

18 / 18 papers shown

Title
NeuBM: Mitigating Model Bias in Graph Neural Networks through Neutral Input Calibration Jiawei Gu Ziyue Qiao Xiao Luo 65 0 0 21 May 2025
Trustworthy Enhanced Multi-view Multi-modal Alzheimer's Disease Prediction with Brain-wide Imaging Transcriptomics Data Shan Cong Zhoujie Fan Hongwei Liu Yinghan Zhang Xin Wang Haoran Luo Xiaohui Yao 42 1 0 21 Jun 2024
Multi-modal Multi-kernel Graph Learning for Autism Prediction and Biomarker Discovery Junbin Mao Jin Liu Han Lin Hulin Kuang Shirui Pan Yi-Lun Pan Shan Xie Fei Liu Yi Pan 26 2 0 03 Mar 2023
NIMFA: A Python Library for Nonnegative Matrix Factorization Marinka Zitnik B. Zupan GNN 17 88 0 06 Aug 2018
Network Enhancement: a general method to denoise weighted biological networks Bo Wang Armin Pourshafeie Marinka Zitnik Junjie Zhu C. Bustamante S. Batzoglou J. Leskovec 11 145 0 09 May 2018
Drug Similarity Integration Through Attentive Multi-view Graph Auto-Encoders Tengfei Ma Cao Xiao Jiayu Zhou Fei Wang 22 163 0 28 Apr 2018
Modeling polypharmacy side effects with graph convolutional networks Marinka Zitnik Monica Agrawal J. Leskovec GNN 51 1,068 0 02 Feb 2018
Representation Learning on Graphs: Methods and Applications William L. Hamilton Rex Ying J. Leskovec GNN 65 1,970 0 17 Sep 2017
Jumping across biomedical contexts using compressive data fusion Marinka Zitnik B. Zupan 24 25 0 10 Aug 2017
Predicting multicellular function through multi-layer tissue networks Marinka Zitnik J. Leskovec 36 538 0 14 Jul 2017
A Closer Look at Memorization in Deep Networks Devansh Arpit Stanislaw Jastrzebski Nicolas Ballas David M. Krueger Emmanuel Bengio ... Tegan Maharaj Asja Fischer Aaron Courville Yoshua Bengio Simon Lacoste-Julien TDI 82 1,801 0 16 Jun 2017
A Unified Approach to Interpreting Model Predictions Scott M. Lundberg Su-In Lee FAtt 36 21,459 0 22 May 2017
DeepGO: Predicting protein functions from sequence and interactions using a deep ontology-aware classifier Maxat Kulmanov Mohammed Asif Khan Robert Hoehndorf 26 391 0 15 May 2017
Understanding Black-box Predictions via Influence Functions Pang Wei Koh Percy Liang TDI 91 2,854 0 14 Mar 2017
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems Martín Abadi Ashish Agarwal P. Barham E. Brevdo Zhiwen Chen ... Pete Warden Martin Wattenberg Martin Wicke Yuan Yu Xiaoqiang Zheng 97 11,135 0 14 Mar 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 100 16,765 0 16 Feb 2016
Data Fusion by Matrix Factorization Marinka Zitnik B. Zupan 38 205 0 02 Jul 2013
Kernelized Bayesian Matrix Factorization M. Gönen Suleiman A. Khan Samuel Kaski 74 100 0 06 Nov 2012