31 citations · 31 across the 4 of their papers we have counts for
4 papers
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…
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…
Discriminative Topological Features Reveal Biological Network Mechanisms
Manuel Middendorf, Etay Ziv, Carter Adams +6
Recent genomic and bioinformatic advances have motivated the development of numerous random network models purporting to describe graphs of biological, technological, and sociologi…
Systematic identification of statistically significant network measures
Etay Ziv, Robin Koytcheff, Manuel Middendorf +1
We present a novel graph embedding space (i.e., a set of measures on graphs) for performing statistical analyses of networks. Key improvements over existing approaches include disc…