Gabor Simko

Network-Based Tools for the Identification of Novel Drug Targets

Analysis of network topology and dynamics holds promise for identifying new sets of potential drug targets. In the past few years, network-based tools have become increasingly important in the identification of novel molecular targets for drug development. Systems-based approaches to predict signal transduction–related drug targets have developed into an especially promising field. Here, we summarize our studies, which indicate that modular bridges and overlaps of protein-protein interaction and signaling networks may be of key importance in future drug design. Intermodular nodes are very efficient in mediating the transmission of perturbations between signaling modules and are important in network cooperation. The analysis of stress-induced rearrangements of the yeast interactome by the ModuLand modularization algorithm indicated that components of modular overlap are key players in cellular adaptation to stress. Signaling crosstalk was much more pronounced in humans than in Caenorhabditis elegans or Drosophila melanogaster in the SignaLink (http://www.SignaLink.org) database, a uniformly curated database of eight major signaling pathways. We also showed that signaling proteins that participate in multiple pathways included multiple established drug targets and drug target candidates. Lastly, we caution that the pervasive overlap of cellular network modules implies that wider use of multitarget drugs to partially inhibit multiple individual proteins will be necessary to modify specific cellular functions, because targeting single proteins for complete disruption usually affects multiple cellular functions with little specificity for a particular process. Tools for analyzing network topology and especially network dynamics have great potential to identify alternative sets of targets for developing multitarget drugs.

Foundation for Model Integration: Semantic Backplane

One of the primary goals of the Adaptive Vehicle Make (AVM) program of DARPA is the construction of a model-based design flow and tool chain, META, that will provide significant productivity increase in the development of complex cyber-physical systems. In model-based design, modeling languages and their underlying semantics play fundamental role in achieving compositionality. A significant challenge in the META design flow is the heterogeneity of the design space. This challenge is compounded by the need for rapidly evolving the design flow and the suite of modeling languages supporting it. Heterogeneity of models and modeling languages is addressed by the development of a model integration language – CyPhy – supporting constructs needed for modeling the interactions among different modeling domains. CyPhy targets simplicity: only those abstractions are imported from the individual modeling domains to CyPhy that are required for expressing relationships across sub-domains. This “semantic interface” between CyPhy and the modeling domains is formally defined, evolved as needed and verified for essential properties (such as well-formedness and invariance). Due to the need for rapid evolvability, defining semantics for CyPhy is not a “one-shot” activity; updates, revisions and extensions are ongoing and their correctness has significant implications on the overall consistency of the META tool chain. The focus of this paper is the methods and tools used for this purpose: the META Semantic Backplane. The Semantic Backplane is based on a mathematical framework provided by term algebra and logics, incorporates a tool suite for specifying, validating and using formal structural and behavioral semantics of modeling languages, and includes a library of metamodels and specifications of model transformations.Copyright

Towards a theory for cyber-physical systems modeling

Modeling the heterogeneous composition of physical, computational and communication systems is an important challenge in engineering Cyber-Physical Systems (CPS), where the major sources of heterogeneity are causality, time semantics, and different physical domains. Classical physical laws capture acausal continuous-time dynamics, thus the behavior of physical systems are inherently characterized by acausal continuous-time equations. On the other hand, computational and communication systems are based on the notion of causality and discrete-time semantics. Connecting the two worlds is challenging, and calls for proper formalization of the composition. In this paper, we discuss a formalism that captures both acausal physical laws, unidirectional analog signals, and is capable of describing causal computational systems, as well as the composition of CPS models.

Specification of Cyber-Physical Components with Formal Semantics --- Integration and Composition

Model-Based Engineering of Cyber-Physical Systems CPS needs correct-by-construction design methodologies, hence CPS modeling languages require mathematically rigorous, unambiguous, and sound specifications of their semantics. The main challenge is the formalization of the heterogeneous composition and interactions of CPS systems. Creating modeling languages that support both the acausal and causal modeling approaches, and which has well-defined and sound behavior across the heterogeneous time domains is a challenging task. In this paper, we discuss the difficulties and as an example develop the formal semantics of a CPS-specific modeling language called CyPhyML. We formalize the structural semantics of CyPhyML by means of constraint rules and its behavioral semantics by defining a semantic mapping to a language for differential algebraic equations. The specification language is based on an executable subset of first-order logic, which facilitates model conformance checking, model checking and model synthesis.

Nodes Having a Major Influence to Break Cooperation Define a Novel Centrality Measure: Game Centrality

Cooperation played a significant role in the self-organization and evolution of living organisms. Both network topology and the initial position of cooperators heavily affect the cooperation of social dilemma games. We developed a novel simulation program package, called ‘NetworGame’, which is able to simulate any type of social dilemma games on any model, or real world networks with any assignment of initial cooperation or defection strategies to network nodes. The ability of initially defecting single nodes to break overall cooperation was called as ‘game centrality’. The efficiency of this measure was verified on well-known social networks, and was extended to ‘protein games’, i.e. the simulation of cooperation between proteins, or their amino acids. Hubs and in particular, party hubs of yeast protein-protein interaction networks had a large influence to convert the cooperation of other nodes to defection. Simulations on methionyl-tRNA synthetase protein structure network indicated an increased influence of nodes belonging to intra-protein signaling pathways on breaking cooperation. The efficiency of single, initially defecting nodes to convert the cooperation of other nodes to defection in social dilemma games may be an important measure to predict the importance of nodes in the integration and regulation of complex systems. Game centrality may help to design more efficient interventions to cellular networks (in forms of drugs), to ecosystems and social networks.

Elimination of clavicle shadows to help automatic lung nodule detection on chest radiographs

Lung nodule detection is one of the most important goals of large scale screening of chest radiographs. The success of nodule detection can be increased if it is possible to suppress the bony structures from the chest radiographs. While one possible way to do this is to use dual-energy imaging, most of the commercial X-ray machines do not offer this technology. Finding an alternative approach is an important task. This paper proposes a new solution for it, where first the contours of bones -especially the contours of clavicles- are detected then the shadow of the bones is removed. The performance of the clavicle suppression algorithm is then evaluated by the use of a nodule detection system. The algorithms were tested on images from the JSRT database. The nodule detection algorithm was looking for up to 20 suspicious areas in the original images. According to our first results in the images with suppressed clavicle shadows 20 of 380 false positives were removed, while all true positives were preserved. 69 of the original 380 false positives were around the clavicle, which would mean 24% decrease in the concerned region.

Diversely enumerating system-level architectures

Embedded systems are highly constrained, and modern constraint solvers can be used to synthesize architectures satisfying constraints. However, solvers may enumerate solutions with bias yielding a skewed view of the solution space. In this paper we formalize enumerators, enumeration bias, and build empirically diverse enumerators. An ideal diverse enumerator uniformly draws equivalence classes of solutions. We develop an algorithm, called symmetry-directed randomized partitioning, for constructing empirically diverse enumerators from modern unmodified constraint solvers. We show that our diverse enumerator is significantly closer to the ideal compared to baseline and randomized solvers.

A bounded model checking tool for periodic sample-hold systems

Safety verification of a plant together with its controller is an important part of controller design. If the controller is implemented in software, then a formal model such as hybrid automata is needed to model the composite system. However, classic hybrid automata scale poorly for complex software controllers due to their eager representation of discrete states. In this paper we present safety verification for software controllers without constructing hybrid automata. Our approach targets a common class of software controllers, where the plant is periodically sampled and actuated by the controller. The resulting systems exhibit a regular alternation of discrete steps and fixed length continuous-time evolution. We show that these systems can be verified by a combination of SMT solving and Taylor models. SMT formulas accurately capture control software in a compact form, and Taylor models accurately capture continuous trajectories up to guaranteed error bounds.

A Framework for Unambiguous and Extensible Specification of DSMLs for Cyber-Physical Systems

Increased emphasis on developing model-based design methods for Cyber-Physical Systems (CPS) brings new challenges to the specification of domain specific modeling languages (DSML) and the integration of heterogeneous CPS components.Since CPS are composed of tightly integrated physical and computational components, the modeled domains include both physical and computational systems.Formal specification of physical and computational languages as well as their integration remains an interesting challenge.In this paper we introduce a formal logic based framework for formal specification and simulation, that is supported by the fixed-point logic language FORMULA.As a representative case study, we define both the structural and behavioral semantics for a bond graph language, and demonstrate the reusability and extensibility provided by the approach by extending the language to support hybrid dynamics.

A CAD System for Screening X-ray Chest Radiography

The paper presents the first results of a Computer Aided Diagnosis (CAD) system development project for automatic evaluation of chest X-ray radiographs. The primary aim of the R&D project is to develop an intelligent advisory system for analyzing chest X-ray images and detecting lung nodules. This work has been started a few years ago and the CAD system will be used as an evaluation module of a digital X-ray lung disease screening system. The main steps of the research and development work is to segment the X-ray images according to the anatomical parts (determining the contours of lung, heart, clavicles and the rib cage) reducing the unwanted shadows (anatomical noise) of the bones and the heart, and detecting nodules and other abnormalities in the chest images. Research tasks are already in an advanced state, algorithms have been developed. First results on a moderate-size database are encouraging and we can expect further advances from the utilization of a large scale clinical testing that will start in the near future.