Cancer metastasis is no longer viewed as a linear cascade of events but rather as a series
of concurrent, partially overlap** processes, as successfully metastasizing cells assume …

Biological entities are involved in intricate and complex interactions, in which uncovering the
biological information from the network concepts are of great significance. Benefiting from …

Cellular interactions can be modeled as complex dynamical systems represented by
weighted graphs. The functionality of such networks, including measures of robustness …

Single-cell omics is transforming our understanding of cell biology and disease, yet the
systems-level analysis and interpretation of single-cell data faces many challenges. In this …

The cellular phenotype is described by a complex network of molecular interactions.
Elucidating network properties that distinguish disease from the healthy cellular state is …

Differentiation is a key cellular process in normal tissue development that is significantly
altered in cancer. Although molecular signatures characterising pluripotency and …

Entropic measures of complexity are able to quantify the information encoded in complex
network structures. Several entropic measures have been proposed in this respect. Here we …

We present a novel regularization scheme called The Generalized Elastic Net (GELnet) that
incorporates gene pathway information into feature selection. The proposed formulation is …

Biomarkers are a class of measurable and evaluable indicators with the potential to predict
disease initiation and progression. In contrast to disease-associated factors, biomarkers …

In estimating the complexity of objects, in particular, of graphs, it is common practice to rely
on graph-and information-theoretic measures. Here, using integer sequences with …