Euglenids exhibit an unconventional motility strategy amongst unicellular eukaryotes, consisting of large-amplitude highly concerted deformations of the entire body (euglenoid movement or metaboly). A plastic cell envelope called pellicle mediates these deformations. Unlike ciliary or flagellar motility, the biophysics of this mode is not well understood, including its efficiency and molecular ...

This paper presents techniques for reverse engineering of re-lational database applications. The target of such an eeort is the deeni-tion of a fully equipped object-oriented view of the relational database, including methods and constraints. Such views can be seen as a full speci-cation of the database semantics, aiding for example in the identiication of semantic heterogeneity among interoper...

Successful reverse engineering needs to take into account human knowledge about architecture, about features or even about validation of the results of automatic analyses. This knowledge should be linked to the automatically reverse engineered model and should be taken into account by analyses. Typically, when we want to reason about data, we first encode an explicit metamodel and then express ...

Network-based intrusion detection systems analyze network traffic looking for evidence of attacks. The analysis is usually performed using signatures, which are rules that describe what traffic should be considered as malicious. If the signatures are known, it is possible to either craft an attack to avoid detection or to send synthetic traffic that will match the signature to over-stimulate th...

Reversible logic has two main properties. First, the number of inputs is equal to the number of outputs. Second, it implements a one-to-one mapping; i.e., one can reconstruct the inputs from the outputs. These properties enable its applications in building quantum computing architectures. In this paper we study reverse engineering of reversible logic circuits, including reverse engineering of n...

We consider the problem of reverse-engineering dynamic models of biochemical networks from experimental data using polynomial dynamic systems. In earlier work, we developed an algorithm to identify minimal wiring diagrams, that is, directed graphs that represent the causal relationships between network variables. Here we extend this algorithm to identify a most likely dynamic model from the set...

One of the greatest aspirations of the human mind has been to realize machines that surpass its cognitive intelligence. The rapid expansion in computing power, about to exceed the equivalent of the human brain, has yet to produce such a machine. The article by Neftci et al. in PNAS (1) offers a refreshing and humbling reminder that the brain’s cognition does not arise from exacting digital prec...

We propose a new design for inspection and reverse engineering environments. We have designed and experimented with such an environinent for capturing sense data of niechaniccil parts in an intelligent way. We construct a sensing -+ CAD interface for the automatic recoiistruction of parts from visual data. We briefly discuss the use of the dynamic recursive finite state machine (DRFSM) as a new...

Microarray technologies, which enable the simultaneous measurement of all RNA transcripts in a cell, have spawned the development of algorithms for reverse-engineering transcription control networks. In this article, we classify the algorithms into two general strategies: physical modeling and influence modeling. We discuss the biological and computational principles underlying each strategy, a...

Reverse engineering the variability of an existing system is a challenging activity. The architect knowledge is essential to identify variation points and explicit constraints between features, for instance in feature models (FMs), but the manual creation of FMs is both timeconsuming and error-prone. On a large scale, it is very difficult for an architect to guarantee that the resulting FM ensu...