35,536 research outputs found
Human-chimpanzee alignment: Ortholog Exponentials and Paralog Power Laws
Genomic subsequences conserved between closely related species such as human
and chimpanzee exhibit an exponential length distribution, in contrast to the
algebraic length distribution observed for sequences shared between distantly
related genomes. We find that the former exponential can be further decomposed
into an exponential component primarily composed of orthologous sequences, and
a truncated algebraic component primarily composed of paralogous sequences.Comment: Main text: 31 pages, 13 figures, 1 table; Supplementary materials: 9
pages, 9 figures, 1 tabl
Refined Holonomic Summation Algorithms in Particle Physics
An improved multi-summation approach is introduced and discussed that enables
one to simultaneously handle indefinite nested sums and products in the setting
of difference rings and holonomic sequences. Relevant mathematics is reviewed
and the underlying advanced difference ring machinery is elaborated upon. The
flexibility of this new toolbox contributed substantially to evaluating
complicated multi-sums coming from particle physics. Illustrative examples of
the functionality of the new software package RhoSum are given.Comment: Modified Proposition 2.1 and Corollary 2.
MonetDB/XQuery: a fast XQuery processor powered by a relational engine
Relational XQuery systems try to re-use mature relational data management infrastructures to create fast and scalable XML database technology. This paper describes the main features, key contributions, and lessons learned while implementing such a system. Its architecture consists of (i) a range-based encoding of XML documents into relational tables, (ii) a compilation technique that translates XQuery into a basic relational algebra, (iii) a restricted (order) property-aware peephole relational query optimization strategy, and (iv) a mapping from XML update statements into relational updates. Thus, this system implements all essential XML database functionalities (rather than a single feature) such that we can learn from the full consequences of our architectural decisions. While implementing this system, we had to extend the state-of-the-art with a number of new technical contributions, such as loop-lifted staircase join and efficient relational query evaluation strategies for XQuery theta-joins with existential semantics. These contributions as well as the architectural lessons learned are also deemed valuable for other relational back-end engines. The performance and scalability of the resulting system is evaluated on the XMark benchmark up to data sizes of 11GB. The performance section also provides an extensive benchmark comparison of all major XMark results published previously, which confirm that the goal of purely relational XQuery processing, namely speed and scalability, was met
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