Fetching the paper…
Reading the bibliography…
Network biology has been successfully used to help reveal complex mechanisms of disease, especially cancer.
Nonparametric estimation from incomplete observations
Edward L Kaplan and Paul Meier · 1958
Earlier work this paper cites.
Hierarchical grouping to optimize an objective function
Joe H Ward Jr · 1963
Earlier work this paper cites.
The symbol grounding problem
Stevan Harnad · 1990
Earlier work this paper cites.
Learning logical definitions from relations
J Ross Quinlan · 1990
Earlier work this paper cites.
Network biology: understanding the cell’s functional organization
Albert-Laszlo Barabasi and Zoltan N Oltvai · 2004
Earlier work this paper cites.
Weighted graph cuts without eigenvectors a multilevel approach
Inderjit S Dhillon, Yuqiang Guan, and Brian Kulis · 2007
Earlier work this paper cites.
Visualizing data using t-sne
Laurens van der Maaten and Geoffrey Hinton · 2008
Earlier work this paper cites.
Supervised risk predictor of breast cancer based on intrinsic subtypes
Joel S Parker, Michael Mullins, Maggie CU Cheang, Samuel Leung, David Voduc, Tammi Vickery, Sherri Davies, Christiane Fauron, Xiaping He, Zhiyuan Hu, et al · 2009
Earlier work this paper cites.
The graph neural network model
Franco Scarselli, Marco Gori, Ah Chung Tsoi, Markus Hagenbuchner, and Gabriele Monfardini · 2009
Earlier work this paper cites.
Network medicine: a network-based approach to human disease
Albert-László Barabási, Natali Gulbahce, and Joseph Loscalzo · 2011
Earlier work this paper cites.
Wavelets on graphs via spectral graph theory
David K Hammond, Pierre Vandergheynst, and Rémi Gribonval · 2011
Earlier work this paper cites.
Basal breast cancer: a complex and deadly molecular subtype
F Bertucci, P Finetti, and D Birnbaum · 2012
Cited alongside, same era.
Comprehensive molecular portraits of human breast tumors
Cancer Genome Atlas Network et al · 2012
Cited alongside, same era.
Comprehensive molecular portraits of human breast tumours
Aleix Prat Aparicio · 2012
Cited alongside, same era.
Spectral networks and locally connected networks on graphs
Joan Bruna, Wojciech Zaremba, Arthur Szlam, and Yann LeCun · 2013
Cited alongside, same era.
Personalizing the treatment of women with early breast cancer: highlights of the st gallen international expert consensus on the primary therapy of early breast cancer 2013
Aron Goldhirsch, Eric P Winer, AS Coates, et al · 2013
Cited alongside, same era.
Gated graph sequence neural networks
Yujia Li, Daniel Tarlow, Marc Brockschmidt, and Richard Zemel · 2015
Later among the works it cites.
The molecular signatures database hallmark gene set collection
Arthur Liberzon, Chet Birger, Helga Thorvaldsdóttir, Mahmoud Ghandi, Jill P Mesirov, and Pablo Tamayo · 2015
Later among the works it cites.
Convolutional neural networks on graphs with fast localized spectral filtering
Michaël Defferrard, Xavier Bresson, and Pierre Vandergheynst · 2016
Later among the works it cites.
Learning graphical state transitions
Daniel D Johnson · 2016
Later among the works it cites.
Learning convolutional neural networks for graphs
Mathias Niepert, Mohamed Ahmed, and Konstantin Kutzkov · 2016
Later among the works it cites.
Geometric deep learning: going beyond euclidean data
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
The emerging field of signal processing on graphs: Extending high-dimensional data analysis to networks and other irregular domains
David I Shuman, Sunil K Narang, Pascal Frossard, Antonio Ortega, and Pierre Vandergheynst · 2013
Cited alongside, same era.
Adam: A method for stochastic optimization
Diederik Kingma and Jimmy Ba · 2014
Cited alongside, same era.
String v10: protein–protein interaction networks, integrated over the tree of life
Damian Szklarczyk, Andrea Franceschini, Stefan Wyder, et al · 2014
Cited alongside, same era.
Deep convolutional networks on graph-structured data
Mikael Henaff, Joan Bruna, and Yann LeCun · 2015
Cited alongside, same era.
Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy · 2015
Cited alongside, same era.
Michael M Bronstein, Joan Bruna, Yann LeCun, Arthur Szlam, and Pierre Vandergheynst · 2017
Closest in time.
Network propagation: a universal amplifier of genetic associations
Lenore Cowen, Trey Ideker, Benjamin J Raphael, and Roded Sharan · 2017
Closest in time.
Svm and svm ensembles in breast cancer prediction
Min-Wei Huang, Chih-Wen Chen, Wei-Chao Lin, Shih-Wen Ke, and Chih-Fong Tsai · 2017
Closest in time.
A simple neural network module for relational reasoning
Adam Santoro, David Raposo, David G Barrett, Mateusz Malinowski, Razvan Pascanu, Peter Battaglia, and Tim Lillicrap · 2017
Closest in time.
Graph attention networks
Petar Veličković, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Liò, and Yoshua Bengio · 2018
Closest in time.