getting started in probabilistic graphical models开始在概率图形模型.pdfVIP

Message From ISCB Getting Started in Probabilistic Graphical Models Edoardo M. Airoldi robabilistic graphical models and computational scientists, and their abundance, functional processes, P (PGMs) have become a popular discusses the aspects to which each and membership of genes to functional tool for computational analysis scientist should contribute to carry out processes. Next we translate the of biological data in a variety of the data analysis successfully using biological players and the connections domains. But, what exactly are they and PGMs. we established among them into how do they work? How can we use Let us start by considering a specific mathematical quantities (i.e., random PGMs to discover patterns that are problem in transcriptional regulation. variables) and connections among biologically relevant? And to what Given measurements about the them (i.e., statistical dependencies). extent can PGMs help us formulate new abundance of gene transcripts in This translation specifies the model hypotheses that are testable at the retinal cells across stages of structure. At this stage, we rely on bench? This Message sketches out some development, we would like to discover biological intuitions to fine-tune the answers and illustrates the main ideas which functional processes are relevant model, for instance, by deciding which behind the statistical approach to for development, and reveal which sources of variability in the biological pattern discovery. ones ar