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  • 1
    Online Resource
    Online Resource
    Oxford University Press (OUP) ; 2012
    In:  Bioinformatics Vol. 28, No. 12 ( 2012-06-15), p. i172-i178
    In: Bioinformatics, Oxford University Press (OUP), Vol. 28, No. 12 ( 2012-06-15), p. i172-i178
    Abstract: Motivation: Shotgun sequence read data derived from xenograft material contains a mixture of reads arising from the host and reads arising from the graft. Classifying the read mixture to separate the two allows for more precise analysis to be performed. Results: We present a technique, with an associated tool Xenome, which performs fast, accurate and specific classification of xenograft-derived sequence read data. We have evaluated it on RNA-Seq data from human, mouse and human-in-mouse xenograft datasets. Availability:  Xenome is available for non-commercial use from http://www.nicta.com.au/bioinformatics Contact:  tom.conway@nicta.com.au
    Type of Medium: Online Resource
    ISSN: 1367-4811 , 1367-4803
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2012
    detail.hit.zdb_id: 1468345-3
    SSG: 12
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  • 2
    Online Resource
    Online Resource
    Oxford University Press (OUP) ; 2012
    In:  Bioinformatics Vol. 28, No. 14 ( 2012-07-15), p. 1937-1938
    In: Bioinformatics, Oxford University Press (OUP), Vol. 28, No. 14 ( 2012-07-15), p. 1937-1938
    Abstract: Motivation: The de novo assembly of short read high-throughput sequencing data poses significant computational challenges. The volume of data is huge; the reads are tiny compared to the underlying sequence, and there are significant numbers of sequencing errors. There are numerous software packages that allow users to assemble short reads, but most are either limited to relatively small genomes (e.g. bacteria) or require large computing infrastructure or employ greedy algorithms and thus often do not yield high-quality results. Results: We have developed Gossamer, an implementation of the de Bruijn approach to assembly that requires close to the theoretical minimum of memory, but still allows efficient processing. Our results show that it is space efficient and produces high-quality assemblies. Availability:  Gossamer is available for non-commercial use from http://www.genomics.csse.unimelb.edu.au/product-gossamer.php. Contact:  tom.conway@nicta.com.au
    Type of Medium: Online Resource
    ISSN: 1367-4811 , 1367-4803
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2012
    detail.hit.zdb_id: 1468345-3
    SSG: 12
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  • 3
    Online Resource
    Online Resource
    Association for Computing Machinery (ACM) ; 2007
    In:  ACM SIGPLAN Notices Vol. 42, No. 9 ( 2007-10), p. 25-28
    In: ACM SIGPLAN Notices, Association for Computing Machinery (ACM), Vol. 42, No. 9 ( 2007-10), p. 25-28
    Abstract: C-Rules is a business rules management system developed by Constraint Technologies International 1 (CTI), designed for use in transportation problems. Users define rules describing various aspects of a problem, such as solution costs and legality, which are then queried from a host application, typically an optimising solver. At its core, C-Rules provides a functional expression language which affords users both power and flexibility when formulating rules. In this paper we will describe our experiences of using functional programming both at the end-user level, as well as at the implementation level. We highlight some of the benefits we, and the product's users, have enjoyed from the decision to base our rule system on features such as: higher-order functions, referential transparency, and static, polymorphic typing. We also outline some of our experiences in using Haskell to build an efficient compiler for the core language.
    Type of Medium: Online Resource
    ISSN: 0362-1340 , 1558-1160
    Language: English
    Publisher: Association for Computing Machinery (ACM)
    Publication Date: 2007
    detail.hit.zdb_id: 2079194-X
    detail.hit.zdb_id: 282422-X
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  • 4
    Online Resource
    Online Resource
    PeerJ ; 2016
    In:  PeerJ Computer Science Vol. 2 ( 2016-07-25), p. e71-
    In: PeerJ Computer Science, PeerJ, Vol. 2 ( 2016-07-25), p. e71-
    Abstract: While traditional methods for calling variants across whole genome sequence data rely on alignment to an appropriate reference sequence, alternative techniques are needed when a suitable reference does not exist. We present a novel alignment and assembly free variant calling method based on information theoretic principles designed to detect variants have strong statistical evidence for their ability to segregate samples in a given dataset. Our method uses the context surrounding a particular nucleotide to define variants. Given a set of reads, we model the probability of observing a given nucleotide conditioned on the surrounding prefix and suffixes of length k as a multinomial distribution. We then estimate which of these contexts are stable intra-sample and varying inter-sample using a statistic based on the Kullback–Leibler divergence. The utility of the variant calling method was evaluated through analysis of a pair of bacterial datasets and a mouse dataset. We found that our variants are highly informative for supervised learning tasks with performance similar to standard reference based calls and another reference free method (DiscoSNP++). Comparisons against reference based calls showed our method was able to capture very similar population structure on the bacterial dataset. The algorithm’s focus on discriminatory variants makes it suitable for many common analysis tasks for organisms that are too diverse to be mapped back to a single reference sequence.
    Type of Medium: Online Resource
    ISSN: 2376-5992
    Language: English
    Publisher: PeerJ
    Publication Date: 2016
    detail.hit.zdb_id: 2868384-5
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  • 5
    Online Resource
    Online Resource
    Cambridge University Press (CUP) ; 2010
    In:  Journal of Functional Programming Vol. 20, No. 2 ( 2010-03), p. 123-136
    In: Journal of Functional Programming, Cambridge University Press (CUP), Vol. 20, No. 2 ( 2010-03), p. 123-136
    Abstract: C-Rules is a business rules management system developed by Constraint Technologies International ( www.constrainttechnologies.com ) that is designed for use in transport, travel and logistics problems. Individual businesses within these industries often need to solve the same kinds of problems related to scheduling of operations, resource allocation, staff rostering and so on, but each organisation has its own rules and procedures. Furthermore, these problems tend to be combinatorially challenging: before a final solution is chosen, many potential choices need to be generated, evaluated and compared. In C-Rules, users define rules that describe various aspects of a problem. These rules can be invoked from an application, which is typically either an optimising solver or an interactive planning tool. Rules can be used to encode evaluation criteria, such as the legality or cost of a proposed solution, or values like configuration parameters that may be used by the host application to tune or direct its progress. At its core, C-Rules provides a functional expression language that affords users power and flexibility when formulating rules. In this paper we will describe our experiences of using functional programming both at the end-user level and at the implementation level. We highlight some of the benefits of basing our rule system on features such as higher-order functions, referential transparency and static, polymorphic typing. We also outline some of our experiences in using Haskell to build an efficient compiler for the core language.
    Type of Medium: Online Resource
    ISSN: 0956-7968 , 1469-7653
    Language: English
    Publisher: Cambridge University Press (CUP)
    Publication Date: 2010
    detail.hit.zdb_id: 1481650-7
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