Type I interferons (IFNs), including various IFN-α isoforms and IFN-β, are a family of
homologous, multifunctional cytokines. IFNs activate different cellular responses by binding …

Abstract Analysis of cellular phenotypes in large imaging data sets conventionally involves
supervised statistical methods, which require user-annotated training data. This paper …

Biological processes involve a variety of spatial and temporal scales. A holistic
understanding of many biological processes therefore requires multi-scale models which …

White matter tractography, based on diffusion-weighted magnetic resonance images, is
currently the only available in vivo method to gather information on the structural brain …

Cells react to nutritional cues in changing environments via the integrated action of
signaling, transcriptional, and metabolic networks. Mechanistic insight into signaling …

We propose unsupervised representation learning and feature extraction from dendrograms.
The commonly used Minimax distance measures correspond to building a dendrogram with …

This paper introduces a method to predict and analyse students' mathematical performance
by detecting distinguishable subgroups of children who share similar learning patterns. We …

We propose a hierarchical correlation clustering method that extends the well-known
correlation clustering to produce hierarchical clusters applicable to both positive and …

Gaussian processes are powerful tools since they can model non-linear dependencies
between inputs, while remaining analytically tractable. A Gaussian process is characterized …

Several clustering methods (eg, Normalized Cut and Ratio Cut) divide the Min Cut cost
function by a cluster dependent factor (eg, the size or the degree of the clusters), in order to …