Background Despite the recognized importance of module discovery in biological networks
to enhance our understanding of complex biological systems, existing methods generally …

The normal and abnormal behavior of a living cell is governed by complex networks of
interacting biomolecules. Models of these networks allow us to make predictions about …

Background The type 1 (microbial) rhodopsins are a diverse group of photochemically
reactive proteins that display a broad yet patchy distribution among the three domains of life …

A fundamental problem in meta-analysis is how to systematically combine information from
multiple statistical tests to rigorously evaluate a single overarching hypothesis. This problem …

Poor prognosis and drug resistance in glioblastoma (GBM) can result from cellular
heterogeneity and treatment-induced shifts in phenotypic states of tumor cells, including …

Mathematical models have many applications in infectious diseases: epidemiologists use
them to forecast outbreaks and design containment strategies; systems biologists use them …

Background Classification using microarray datasets is usually based on a small number of
samples for which tens of thousands of gene expression measurements have been …

Current methods for reconstructing biological networks often learn either the topology of
large networks or the kinetic parameters of smaller networks with a well-characterized …

Network alignment refers to the problem of finding a bijective mapping across vertices of two
or more graphs to maximize the number of overlapping edges and/or to minimize the …

Background Cells dynamically adapt their gene expression patterns in response to various
stimuli. This response is orchestrated into a number of gene expression modules consisting …