The functions and morphology of cellular membranes are intimately related and depend not only on their protein content but also on the repertoire of lipids that comprise them. In the absence of in vivo data on lipid asymmetry in endomembranes, it has been argued that motors, scaffolding proteins or integral membrane proteins rather than non-lamellar bilayer lipids such as diacylglycerol (DAG), ...

Rationale: Fetuses that develop in diabetic mothers have a higher incidence of birth defects that include cardiovascular defects, but the signaling pathways that mediate these developmental effects are poorly understood. It is reasonable to hypothesize that diabetic maternal effects are mediated by 1 or more pathways activated downstream of aberrant glucose metabolism, because poorly controlled...

The manipulation of signals downstream of the TCR can have profound consequences for T cell development, function, and homeostasis. Diacylglycerol (DAG) produced after TCR stimulation functions as a secondary messenger and mediates the signaling to Ras-MEK-Erk and NF-κB pathways in T cells. DAG kinases (DGKs) convert DAG into phosphatidic acid, resulting in termination of DAG signaling. In this...

We extend the language of influence diagrams to cope with decision scenarios where the order of decisions and observations is not determined. As the ordering of decisions is dependent on the evidence, a step-strategy of such a scenario is a sequence of dependent choices of the next action. A strategy is a step-strategy together with selection functions for decision actions. The structure of a s...

To build a Bayesian network, one may directly construct a directed acyclic graph (DAG) based on causal relationship of the domain variables. However, it may be necessary in many applications to construct a DAG from conditional independencies (CIs). In this paper, we characterize CIs that can be represented by a perfect DAG and suggest an algorithm to construct such a DAG, provided that the give...

Directed acyclic graph (DAG) models are popular tools for describing causal relationships and for guiding attempts to learn them from data. In particular, they appear to supply a means of extracting causal conclusions from probabilistic conditional independence properties inferred from purely observational data. I take a critical look at this enterprise, and suggest that it is in need of more, ...

Recursive max-linear vectors model causal dependence between node variables by a structural equation model, expressing each variable as function of its parental nodes in directed acyclic graph (DAG) and some exogenous innovation. For such there exists unique minimum DAG, represented the Kleene star matrix edge weight matrix, which identifies can be estimated. more realistic statistical modeling...