Abstract The effects of tumor-associated neutrophils (TANs) on glioblastoma biology remain poorly understood. Flow cytometric analysis 5 newly diagnosed fresh tissue specimens surprisingly revealed a high fraction (21.0-34.1%) TANs expressed MHCII, marker antigen-presenting cells not classically associated with and in matched peripheral blood (PBNs). Transcriptomic profiling confirmed that pati...

Probabilistic Boolean networks (PBNs) is a well-established computational framework for modelling biological systems. The steady-state dynamics of PBNs is of crucial importance in the study of such systems. However, for large PBNs, which often arise in systems biology, obtaining the steady-state distribution poses a significant challenge. In fact, statistical methods for steady-state approximat...

MOTIVATION Our goal is to construct a model for genetic regulatory networks such that the model class: (i) incorporates rule-based dependencies between genes; (ii) allows the systematic study of global network dynamics; (iii) is able to cope with uncertainty, both in the data and the model selection; and (iv) permits the quantification of the relative influence and sensitivity of genes in their...

Class-level dependencies model general relational statistics over attributes of linked objects and links. Class-level relationships are important in themselves, and they support applications like policy making, strategic planning, and query optimization. An example of a class-level query is “what is the percentage of friendship pairs where both friends are women?”. To represent class-level stat...

MOTIVATION Intervention in a gene regulatory network is used to help it avoid undesirable states, such as those associated with a disease. Several types of intervention have been studied in the framework of a probabilistic Boolean network (PBN), which is essentially a finite collection of Boolean networks in which at any discrete time point the gene state vector transitions according to the rul...

We study the problem of finding optimal control policies for Probabilistic Boolean Networks (PBNs). Boolean Networks (BNs) and PBNs are effective tools for modeling genetic regulatory networks. A PBN is a collection of BNs driven by a Markov chain process. It is well-known that the control/intervention of a genetic regulatory network is useful for avoiding undesirable states associated with dis...

Modeling gene regulation is an important problem in genomic research. Boolean networks (BN) and its generalization Probabilistic Boolean networks (PBNs) have been proposed to model genetic regulatory interactions. BN is a deterministic model while PBN is a stochastic model. In a PBN, on one hand, its stationary distribution gives important information about the long-run behavior of the network....

Our goal is to develop an algorithm for the automated study of the dynamics of Probabilistic Boolean Network (PBN) representation of genes. Model checking is an automated method for the verification of properties on systems. Continuous Stochastic Logic (CSL), an extension of Computation Tree Logic (CTL), is a model-checking tool that can be used to specify measures for Continuous-time Markov Ch...

Methoxymethylation of a variety of alcohols was performed using formaldehyde dimethyl acetal in the presence of 1,3-dichloro-5,5-dimethyl hydantoin [DCDMH] and Poly N,N′-dibromo-N-ethyl naphthyl-2,7-disulfonamide [PBNS] as catalysts at room temperature and under solvent-free conditions. Our experiments show that primary and secondary alcohols can be smoothly converted into the corresponding MOM...