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Qualitative dynamics semantics for SBGN process description
Background Qualitative dynamics semantics provide a coarse-grain modeling of networks dynamics by abstracting away kinetic parameters. They allow to capture general features of... -
ARN: analysis and prediction by adipogenic professional database
Adipogenesis is the process of cell differentiation by which mesenchymal stem cells become adipocytes. Extensive research is ongoing to identify genes, their protein products,... -
DGCA: A comprehensive R package for Differential Gene Correlation Analysis
Background Dissecting the regulatory relationships between genes is a critical step towards building accurate predictive models of biological systems. A powerful approach... -
A physarum-inspired prize-collecting steiner tree approach to identify subnet...
Background Drug repositioning can reduce the time, costs and risks of drug development by identifying new therapeutic effects for known drugs. It is challenging to reposition... -
SBMLsqueezer 2: context-sensitive creation of kinetic equations in biochemica...
Background The size and complexity of published biochemical network reconstructions are steadily increasing, expanding the potential scale of derived computational models.... -
Classification of breast cancer patients using somatic mutation profiles and ...
Background The high degree of heterogeneity observed in breast cancers makes it very difficult to classify the cancer patients into distinct clinical subgroups and consequently... -
petal: Co-expression network modelling in R
Background Networks provide effective models to study complex biological systems, such as gene and protein interaction networks. With the advent of new sequencing technologies,... -
DNetDB: The human disease network database based on dysfunctional regulation ...
Disease similarity study provides new insights into disease taxonomy, pathogenesis, which plays a guiding role in diagnosis and treatment. The early studies were limited to... -
Robust sparse canonical correlation analysis
Background Canonical correlation analysis (CCA) is a multivariate statistical method which describes the associations between two sets of variables. The objective is to find... -
Gene-microRNA network module analysis for ovarian cancer
Background MicroRNAs (miRNAs) are involved in many biological processes by regulating post-transcriptional gene expression. The alterations of the regulatory pathways can cause...
