2.5k citations · 2.5k across the 8 of their papers we have counts for
4 papers · 1 filter
Predicting Genetic Regulatory Response Using Classification
Manuel Middendorf, Anshul Kundaje, Chris Wiggins +2
We present a novel classification-based method for learning to predict gene regulatory response. Our approach is motivated by the hypothesis that in simple organisms such as Saccha…
ARACNE: An Algorithm for the Reconstruction of Gene Regulatory Networks in a Mammalian Cellular Context
Adam A. Margolin, Ilya Nemenman, Katia Basso +5
Background: Elucidating gene regulatory networks is crucial for understanding normal cell physiology and complex pathologic phenotypes. Existing computational methods for the genom…
On The Reconstruction of Interaction Networks with Applications to Transcriptional Regulation
Adam A. Margolin, Ilya Nemenman, Chris Wiggins +2
A novel information-theoretic method for reconstruction of interaction networks is introduced. We prove that the method is exact for some class of networks. Performance tests on la…
Predicting Genetic Regulatory Response using Classification: Yeast Stress Response
Manuel Middendorf, Anshul Kundaje, Chris Wiggins +2
We present a novel classification-based algorithm called GeneClass for learning to predict gene regulatory response. Our approach is motivated by the hypothesis that in simple orga…