David J. John

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Signal transduction networks are crucial for inter- and intra-cellular signaling. Signals are often transmitted via covalent modification of protein structure, with phosphorylation/dephosphorylation as the primary example. In this paper, we apply a recently described method of computational algebra to the modeling of signaling networks, based on time-course(More)
An evolutionary process encourages a system to change, and hopefully improve, based on environmental feed-back. When applied to a computer system, an evolutionary inspired process can be used to discover computer configurations that are different and potentially more secure. These configurations can be instantiated at different times to create a Moving(More)
A Moving Target (MT) defense constantly changes a system's attack surface, in an attempt to limit the usefulness of the reconnaissance the attacker has collected. One approach to this defense strategy is to intermittently change a system's configuration. These changes must maintain functionality and security, while also being diverse. Finding suitable(More)
Clustering analysis is an important exploratory tool that aids in the analysis and organization of genomic data. Each biological data set has different characteris, and the decision of which clustering method is appropriate and how many clusters are optimal on a dataset-by-dataset basis can be problematic. The Figure of Merit (FOM) is a quantitative(More)
Modeling of biological networks is a difficult endeavor, but exploration of this problem is essential for understanding the systems behavior of biological processes. In this contribution, developed for sparse data, we present a new continuous Bayesian graphical learning algorithm to cotemporally model proteins in signaling networks and genes in(More)
An interdisciplinary bioinformatics course has been taught at Wake Forest for three semesters. Undergraduate and graduate students from multiple academic specialties are brought together in a single classroom. In addition to focusing on traditional bioinformatics topics, this course concentrates on interdisciplinary collaboration in the in-class exercises(More)
Algorithms that construct protein interaction models are sensitive to variation in the experimentally derived data presented to them. Variation is introduced in the biology, the experiment, the measurement and the algorithm. This paper introduces a methodology for the analysis of the sensitivity of a given modeling algorithm to the time and individual(More)
Reconstructing networks from time series data is a difficult inverse problem. We apply two methods to this problem using co-temporal functions. Co-temporal functions capture mathematical invariants over time series data. Two modeling techniques for co-temporal networks, one based on algebraic techniques and the other on Bayesian inference, are compared and(More)
Simply stated, the Job Shop Scheduling Problem (JSSP) finds a minimum time schedule given M machines and J jobs. Each job consists of a sequence of tasks, and every task requires one of the M machines for a fixed duration of time. A schedule is an assignment of all the tasks to the machines with the properties (1) the tasks for a particular job execute in(More)