691 citations · 1k across the 11 of their papers we have counts for
5 papers · 1 filter
Learning quantitative sequence-function relationships from massively parallel experiments
Gurinder S. Atwal, Justin B. Kinney
A fundamental aspect of biological information processing is the ubiquity of sequence-function relationships -- functions that map the sequence of DNA, RNA, or protein to a biochem…
Equitability, mutual information, and the maximal information coefficient
Justin B. Kinney, Gurinder S. Atwal
Reshef et al. recently proposed a new statistical measure, the "maximal information coefficient" (MIC), for quantifying arbitrary dependencies between pairs of stochastic quantitie…
Parametric inference in the large data limit using maximally informative models
Justin B. Kinney, Gurinder S. Atwal
Motivated by data-rich experiments in transcriptional regulation and sensory neuroscience, we consider the following general problem in statistical inference. When exposed to a hig…
Information based clustering
Noam Slonim, Gurinder Singh Atwal, Gasper Tkacik +1
In an age of increasingly large data sets, investigators in many different disciplines have turned to clustering as a tool for data analysis and exploration. Existing clustering me…
Information based clustering: Supplementary material
Noam Slonim, Gurinder Singh Atwal, Gasper Tkacik +1
This technical report provides the supplementary material for a paper entitled "Information based clustering", to appear shortly in Proceedings of the National Academy of Sciences…