176 citations · 510 across the 8 of their papers we have counts for
8 papers
Challenges and perspectives in computational deconvolution of genomics data
Lana X. Garmire, Yijun Li, Qianhui Huang +6
Deciphering cell type heterogeneity is crucial for systematically understanding tissue homeostasis and its dysregulation in diseases. Computational deconvolution is an efficient ap…
Increased signaling entropy in cancer requires the scale-free property of protein interaction networks
Andrew E. Teschendorff, Christopher R. S. Banerji, Simone Severini +2
One of the key characteristics of cancer cells is an increased phenotypic plasticity, driven by underlying genetic and epigenetic perturbations. However, at a systems-level it is u…
Signalling Entropy: a novel network-theoretical framework for systems analysis and interpretation of functional omic data
Andrew Teschendorff, Peter Sollich, Reimer Kuehn
A key challenge in systems biology is the elucidation of the underlying principles, or fundamental laws, which determine the cellular phenotype. Understanding how these fundamental…
Cellular network entropy as the energy potential in Waddington's differentiation landscape
Christopher R. S. Banerji, Diego Miranda-Saavedra, Simone Severini +4
Differentiation is a key cellular process in normal tissue development that is significantly altered in cancer. Although molecular signatures characterising pluripotency and multip…
Network Transfer Entropy and Metric Space for Causality Inference
Christopher R. S. Banerji, Simone Severini, Andrew E. Teschendorff
A measure is derived to quantify directed information transfer between pairs of vertices in a weighted network, over paths of a specified maximal length. Our approach employs a gen…
On dynamic network entropy in cancer
James West, Ginestra Bianconi, Simone Severini +1
The cellular phenotype is described by a complex network of molecular interactions. Elucidating network properties that distinguish disease from the healthy cellular state is there…
Approximate entropy of network parameters
James West, Lucas Lacasa, Simone Severini +1
We study the notion of approximate entropy within the framework of network theory. Approximate entropy is an uncertainty measure originally proposed in the context of dynamical sys…
Increased entropy of signal transduction in the cancer metastasis phenotype
Andrew Teschendorff, Simone Severini
Studies into the statistical properties of biological networks have led to important biological insights, such as the presence of hubs and hierarchical modularity. There is also a…