The portable UNIX programming system (PUPS) and CANTOR: a computational environment for dynamical representation and analysis of complex neurobiological data

Many problems in analytical biology, such as the classification of organism s, the modelling of macromolecules, or the structural analysis of metabolic or neural networks, involve complex relational data. Here, we describe a s oftware environment, the portable UNIX programming system (PUPS), which has been developed to allow efficient computational representation and analysi s of such data. The system can also be used as a general development tool f or database and classification applications. As the complexity of analytica l biology problems may lead to computation times of several days or weeks e ven on powerful computer hardware, the PUPS environment gives support for p ersistent computations by providing mechanisms for dynamic interaction and homeostatic protection of processes. Biological objects and their interrela tions are also represented in a homeostatic way in PUPS. Object relationshi ps are maintained and updated by the objects themselves, thus providing a f lexible, scalable and current data representation. Based on the PUPS enviro nment, we have developed an optimization package, CANTOR, which can be appl ied to a wide range of relational data and which has been employed in diffe rent analyses of neuroanatomical connectivity. The CANTOR package makes use of the PUPS system features by modifying candidate arrangements of objects within the system's database. This restructuring is carried out via optimi zation algorithms that are based on user-defined cost functions, thus provi ding flexible and powerful tools for the structural analysis of the databas e content. The use of stochastic optimization also enables the CANTOR syste m to deal effectively with incomplete and inconsistent data. Prototypical f orms of PUPS and CANTOR have been coded and used successfully in the analys is of anatomical and functional mammalian brain connectivity, involving com plex and inconsistent experimental data. In addition, PUPS has been used fo r solving multivariate engineering optimization problems and to implement t he digital identification system (DAISY), a system for the automated classi fication of biological objects. PUPS is implemented in ANSI-C under the POS IX.1 standard and is to a great extent architecture- and operating-system i ndependent. The software is supported by systems libraries that allow multi -threading (the concurrent processing of several database operations), as w ell as the distribution of the dynamic data objects and library operations over clusters of computers. These attributes make the system easily scalabl e, and in principle allow the representation and analysis of arbitrarily la rge sets of relational data. PUPS and CANTOR are freely distributed (http:/ /www.pups.org.uk) as open-source software under the GNU license agreement.