Background: Microarray technology has unveiled transcriptomic differences among tumors of various phenotypes, and, especially, brought great progress in molecular understanding of...
Atsushi Niida, Andrew D. Smith, Seiya Imoto, Shuic...
— In this paper we address the problem of predicting gene activities by finding gene regulatory dependencies in experimental DNA microarray data. Only few approaches to infer th...
Christian Spieth, Felix Streichert, Nora Speer, Ch...
This position paper argues that the operational modelling approaches from the formal methods community can be applied fruitfully within the systems biology domain. The results can ...
Nicola Bonzanni, K. Anton Feenstra, Wan Fokkink, E...
This article deals with the identification of gene regulatory networks from experimental data using a statistical machine learning approach. A stochastic model of gene interactio...
Background: Correlations between polymorphic markers and observed phenotypes provide the basis for mapping traits in quantitative genetics. When the phenotype is gene expression, ...