The formation of vascular networks in vitro develops along two rather distinct stages: during the early migration-dominated stage the main features of the pattern emerge, later the mechanical interaction of the cells with the substratum stretches the network. Mathematical models in the relevant literature have been focusing just on either of the aspects of this complex system. In this paper, a unified view of the morphogenetic process is provided in terms of physical mechanisms and mathematical modeling.

Certain notions concerning physical frames thought as geometrical support of continuous systems are discussed; from these notions, independently from the continuum dynamics, the Cauchy problem for the first order characteristics of the frame, as well as the associated (involutive) compatibility conditions, involving only the initial data, are considered.

In [M. Pedicini and F. Quaglia. A parallel implementation for optimal lambda-calculus reduction PPDP '00: Proceedings of the 2nd ACM SIGPLAN international conference on Principles and practice of declarative programming, pages 3–14, ACM, 2000, M. Pedicini and F. Quaglia. PELCR: Parallel environment for optimal lambda-calculus reduction. CoRR, cs.LO/0407055, accepted for publication on TOCL, ACM, 2005], PELCR has been introduced as an implementation derived from the Geometry of Interaction in order to perform virtual reduction on parallel/distributed computing systems. In this paper we provide an extension of PELCR with computational effects based on directed virtual reduction [V. Danos, M. Pedicini, and L. Regnier. Directed virtual reductions. In M. Bezem D. van Dalen, editor, LNCS 1258, pages 76–88. EACSL, Springer Verlag, 1997], namely a restriction of virtual reduction [V. Danos and L. Regnier. Local and asynchronous beta-reduction (an analysis of Girard's EX-formula). LICS, pages 296–306. IEEE Computer Society Press, 1993], which is a particular way to compute the Geometry of Interaction [J.-Y. Girard. Geometry of interaction 1: Interpretation of system F. In R. Ferro, et al. editors Logic Colloquium '88, pages 221–260. North-Holland, 1989] in analogy with Lamping's optimal reduction [J. Lamping. An algorithm for optimal lambda calculus reduction. In Proc. of 17th Annual ACM Symposium on Principles of Programming Languages. ACM, San Francisco, California, pages 16–30, 1990]. Moreover, the proposed solution preserves scalability of the parallelism arising from local and asynchronous reduction as studied in [M. Pedicini and F. Quaglia. PELCR: Parallel environment for optimal lambda-calculus reduction. CoRR, cs.LO/0407055, accepted for publication on TOCL, ACM, 2005].

Il questo lavoro viene presentato un algoritmo euristico basato su ricerca locale per graph coloring.

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Breve storia degli strumenti per il Calcolo scientifico seguendo un percorso tra i musei italiani che espongono materiali ad essi relativi.

In recent years, the development of high throughput devices for the massive parallel analyses of genomic data has lead to the generation of large amount of new biological evidences and has triggered the proliferation of data mining algorithms for the extraction of meaningful information. Microarrays for gene expression analyses are part of this revolution and provide important insight in molecular biology often in the form of coherent sets of genes representing previously uncharacterized processes. Large amount of data are continuously produced in this form, and computational approaches can significantly improve the efficient use of these results, since comparison among numbers of genes sets can give new meaningful information at no cost from the experimental biology point of view. To address this opportunity we designed and implemented FIT, a scalable, unsupervised algorithm that quantitatively compares different populations of gene sets using two distinct measures of similarity between any two gene sets. These measures are then used to obtain a summary statistic that describes the tightness of fit between sets belonging to two distinct populations of gene sets. We present the results of FIT on two data sets for the study of Lymphoma and Acute Lymphoblastic Leukemia. In both cases FIT was able to recapitulate the previous analyses on these datasets, to extend the results and to extract information likely to offer potential insights into the underlying biology.

The massive production of biological data by means of highly parallel devices like microarrays for gene expression has paved the way to new possible approaches in molecular genetics. Among them the possibility of inferring biological answers by querying large amounts of expression data. Based on this principle, we present here TOM, a web-based resource for the efficient extraction of candidate genes for hereditary diseases. The service requires the previous knowledge of at least another gene responsible for the disease and the linkage area, or else of two disease associated genetic intervals. The algorithm uses the information stored in public resources, including mapping, expression and functional databases. Given the queries, TOM will select and list one or more candidate genes. This approach allows the geneticist to bypass the costly and time consuming tracing of genetic markers through entire families and might improve the chance of identifying disease genes, particularly for rare diseases. We present here the tool and the results obtained on known benchmark and on hereditary predisposition to familial thyroid cancer. Our algorithm is available at http://www-micrel.deis.unibo.it/similar to tom/.

The importance of circuits and systems for high-throughput biological data acquisition in biomedical research are discussed. High-throughput biological data acquisition and processing technologies have shifted the focus of biological research from the the traditional experimental science to that of information science. Powerful computation and communication means can be applied to a very large amount of apparently incoherent data coming from biomedical research. The concept of Laboratory on Chip (LoC) is the natural evolution of System on Chip (SoC) by using an array of heterogeneous technologies. DNA sequencing is the process of finding the exact sequence of bases in a DNA sample and with sequencing it has been possible to determine the gene structure of homo sapiens and other species. In ISFET technology transistor arrays are fabricated and electrical readout circuits can provide a direct measure of the gene expression levels.