Gamma-based clustering via ordered means with application to gene-expression analysis

Discrete mixture models provide a well-known basis for effective clustering algorithms, although technical challenges have limited their scope. In the context of gene-expression data analysis, a model is presented that mixes over a finite catalog of structures, each one representing equality and inequality constraints among latent expected values. Computations depend on the probability that independent gamma-distributed variables attain each of their possible orderings. Each ordering event is equivalent to an event in independent negative-binomial random variables, and this finding guides a dynamic-programming calculation. The structuring of mixture-model components according to constraints among latent means leads to strict concavity of the mixture log likelihood. In addition to its beneficial numerical properties, the clustering method shows promising results in an empirical study.Comment: Published in at http://dx.doi.org/10.1214/10-AOS805 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Two Case Studies of Subsystem Design for General-Purpose CSCW Software Architectures

This paper discusses subsystem design guidelines for the software architecture of general-purpose computer supported cooperative work systems, i.e., systems that are designed to be applicable in various application areas requiring explicit collaboration support. In our opinion, guidelines for subsystem level design are rarely given most guidelines currently given apply to the programming language level. We extract guidelines from a case study of the redesign and extension of an advanced commercial workflow management system and place them into the context of existing software engineering research. The guidelines are then validated against the design decisions made in the construction of a widely used web-based groupware system. Our approach is based on the well-known distinction between essential (logical) and physical architectures. We show how essential architecture design can be based on a direct mapping of abstract functional concepts as found in general-purpose systems to modules in the essential architecture. The essential architecture is next mapped to a physical architecture by applying software clustering and replication to achieve the required distribution and performance characteristics

Cherenkov Telescope Array Data Management

Very High Energy gamma-ray astronomy with the Cherenkov Telescope Array (CTA) is evolving towards the model of a public observatory. Handling, processing and archiving the large amount of data generated by the CTA instruments and delivering scientific products are some of the challenges in designing the CTA Data Management. The participation of scientists from within CTA Consortium and from the greater worldwide scientific community necessitates a sophisticated scientific analysis system capable of providing unified and efficient user access to data, software and computing resources. Data Management is designed to respond to three main issues: (i) the treatment and flow of data from remote telescopes; (ii) "big-data" archiving and processing; (iii) and open data access. In this communication the overall technical design of the CTA Data Management, current major developments and prototypes are presented.Comment: 8 pages, 2 figures, In Proceedings of the 34th International Cosmic Ray Conference (ICRC2015), The Hague, The Netherlands. All CTA contributions at arXiv:1508.0589