The BioModelAnalyzer (BMA) is a web based tool for the development of discrete models of biological systems. Through a graphical user interface, it allows rapid development of complex models of gene and protein interaction networks and stability analysis without requiring users to be proficient computer programmers. Whilst stability is a useful specification for testing many systems, testing temporal specifications in BMA presently requires the user to perform simulations. Here we describe the LTL module, which includes a graphical and natural language interfaces to testing LTL queries. The graphical interface allows for graphical construction of the queries and presents results visually in keeping with the current style of BMA. The Natural language interface complements the graphical interface by allowing a gentler introduction to formal logic and exposing educational resources.

Chronic Myeloid Leukemia (CML) represents a paradigm for the wider cancer field. Despite the fact that tyrosine kinase inhibitors have established targeted molecular therapy in CML, patients often face the risk of developing drug resistance, caused by mutations and/or activation of alternative cellular pathways. To optimize drug development, one needs to systematically test all possible combinations of drug targets within the genetic network that regulates the disease. The BioModelAnalyzer (BMA) is a user-friendly computational tool that allows us to do exactly that. We used BMA to build a CML network-model composed of 54 nodes linked by 104 interactions that encapsulates experimental data collected from 160 publications. While previous studies were limited by their focus on a single pathway or cellular process, our executable model allowed us to probe dynamic interactions between multiple pathways and cellular outcomes, suggest new combinatorial therapeutic targets and highlight previously unexplored sensitivities to Interleukin-3.

Representing a new class of tool for biological modeling, Bio Model Analyzer (BMA) uses sophisticated computational techniques to determine stabilization in cellular networks. This paper presents designs aimed at easing the problems that can arise when such techniques - \'14using distinct approaches to conceptualizing networks\'14 - are applied in biology. The work also engages with more fundamental issues being discussed in the philosophy of science and science studies. It shows how scientific ways of knowing are constituted in routine interactions with tools like BMA, where the emphasis is on the practical business at hand, even when seemingly deep conceptual problems exist. For design, this perspective refigures the frictions raised when computation is used to model biology. Rather than obstacles, they can be seen as opportunities for opening up different ways of knowing.

BioModel Analyzer (bma) is a tool for modeling and analyzing biological networks. Designed with a lightweight graphical user interface, the tool facilitates usage for biologists with no previous knowledge in programming or formal methods. The current implementation analyzes systems to establish stabilization. The results of the analysis--whether they be proofs or counterexamples--are represented visually. This paper describes the approach to modeling used in bma and also notes soon-to-be-released extensions to the tool.