Feature context-dependency and complexity-reduction in probability landscapes for integrative genomics

We demonstrate here how feature context-dependency can be systematically investigated using probability landscapes. Furthermore, we show how different feature probability profiles can be conditionally collapsed to reduce the computational and formal, mathematical complexity of probability landscapes. Interestingly, the possibility of complexity reduction can be linked directly to the analysis of context-dependency.These two advances in our understanding of the properties of probability landscapes not only simplify subsequent cross-correlation analysis in hypothesis-driven model building and testing, but also provide additional insights into the biological gene regulatory problems studied. Furthermore, insights into the nature of individual features and a classification of features according to their minimal context-dependency are achieved. The formal structure proposed contributes to a concrete and tangible basis for attempting to formulate novel mathematical structures for describing gene regulation in eukaryotes on a genome-wide scale.The deciphering of the gene regulatory code of eukaryotic cells and the inference of gene regulatory programs belong to the computationally "hard" problems that are very probably insoluble without using very large collections of experimental genome activity recordings under many different biological conditions in conjunction with empirical gene structure and function annotations [1-4]. Genomic sequence, gene structure and function annotation, as well as functional genomics experimental data, are of heterogeneous nature. In order to conceive computationally efficient algorithms capable of statistical integration of these different types of information, transformations of the different types of data into a continuous and homogeneous data structure have to be developed. We have recently proposed such a concept, which we refer to as probability landscapes [5]. Briefly, we have shown on theoretical grounds how any type of observable quant