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  • 1
    Online Resource
    Online Resource
    Elsevier BV ; 2006
    In:  IFAC Proceedings Volumes Vol. 39, No. 3 ( 2006), p. 113-117
    In: IFAC Proceedings Volumes, Elsevier BV, Vol. 39, No. 3 ( 2006), p. 113-117
    Type of Medium: Online Resource
    ISSN: 1474-6670
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2006
    detail.hit.zdb_id: 2976778-7
    detail.hit.zdb_id: 2839185-8
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  • 2
    Online Resource
    Online Resource
    Centre pour la Communication Scientifique Directe (CCSD) ; 2010
    In:  Discrete Mathematics & Theoretical Computer Science Vol. DMTCS Proceedings vol. AM,..., No. Proceedings ( 2010-01-01)
    In: Discrete Mathematics & Theoretical Computer Science, Centre pour la Communication Scientifique Directe (CCSD), Vol. DMTCS Proceedings vol. AM,..., No. Proceedings ( 2010-01-01)
    Abstract: In this paper we obtain the expectation and variance of the number of Euler tours of a random $d$-in/$d$-out directed graph, for $d \geq 2$. We use this to obtain the asymptotic distribution and prove a concentration result. We are then able to show that a very simple approach for uniform sampling or approximately counting Euler tours yields algorithms running in expected polynomial time for almost every $d$-in/$d$-out graph. We make use of the BEST theorem of de Bruijn, van Aardenne-Ehrenfest, Smith and Tutte, which shows that the number of Euler tours of a $d$-in/$d$-out graph is the product of the number of arborescences and the term $[(d-1)!]^n/n$. Therefore most of our effort is towards estimating the asymptotic distribution of the number of arborescences of a random $d$-in/$d$-out graph.
    Type of Medium: Online Resource
    ISSN: 1365-8050
    Language: English
    Publisher: Centre pour la Communication Scientifique Directe (CCSD)
    Publication Date: 2010
    detail.hit.zdb_id: 1412155-4
    SSG: 17,1
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  • 3
    Online Resource
    Online Resource
    Elsevier BV ; 2009
    In:  Journal of Discrete Algorithms Vol. 7, No. 2 ( 2009-06), p. 168-180
    In: Journal of Discrete Algorithms, Elsevier BV, Vol. 7, No. 2 ( 2009-06), p. 168-180
    Type of Medium: Online Resource
    ISSN: 1570-8667
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2009
    detail.hit.zdb_id: 2133801-2
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  • 4
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 83, No. 7_Supplement ( 2023-04-04), p. 6602-6602
    Abstract: Liquid biopsy for profiling of cell free DNA (cfDNA) in blood holds huge promise to transform how we experience and manage cancer by early detection and identification of residual disease and subtype. However, a standard blood draw yields an average of only 10 ng of cfDNA, of which DNA derived from the tumor is a small minority. Therefore, we are faced with a dilemma when utilizing the limited sample to obtain maximum information. Genetic sequencing provides information on actionable somatic mutations but detection of a few loci in a minority of the sample is challenging. Modified cytosine profiles of cancer are differential from non-cancer at many more loci and so provide a stronger signal. Moreover, they can be used to distinguish tissue-of-origin of the tumor. However, methods such as bisulfite sequencing, EM-seq and TAPS sacrifice genetic information (namely C- & gt;T mutations, which are the most common mutation in cancer) to measure modified cytosine. Genetic and modified cytosine data together have been shown to be more powerful for the detection of early cancer than either alone. Here we present a technology, which sequences at base resolution the complete genetic sequence integrated with modified cytosine from low nanogram amounts of cfDNA. It consists of (i) a single pre-sequencing workflow, which creates a copy of the original DNA and performs enzymatic base conversions which discriminate genetic and epigenetic states and (ii) post-sequencing data processing which resolves the resultant sequencing data to an information-rich 16-state code and derives genetic variants integrated with modified cytosine levels, within easy-to-use software. It is, in principle, compatible with any sequencing methodology and is shown here optimized for the Illumina fleet. In cfDNA we show accuracy of modC measurement is higher than that of bisulfite sequencing and EM-seq; and the accuracy of genetic sequencing is higher than that of Illumina alone. Accuracy of measurement is extremely important for liquid biopsy where tumor DNA is in the minority and observed in a small number of reads. We demonstrate the impact of varying base calling error rate on limit of detection for rare alleles in cfDNA samples. Further we show derivation of cfDNA fragment characteristics and that this is produced in combination with genetic and modC information. This further increases the signal available from cfDNA in only one workflow. We suggest this method will help advance the field of liquid biopsy towards its promise. Citation Format: Fabio Puddu, Casper K. Lumby, Nick Harding, David J. Morley, Jamie Scotcher, Robert Crawford, Jens Füllgrabe, Walraj S. Gosal, Shirong Yu, Daniel Brudzewsky, Jane Haywood, Andrada Tomoni, Philippa Burns, Joanna D. Holbrook, Paidi Creed. Refining liquid biopsy: generating more information from cell free DNA [abstract] . In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6602.
    Type of Medium: Online Resource
    ISSN: 1538-7445
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2023
    detail.hit.zdb_id: 2036785-5
    detail.hit.zdb_id: 1432-1
    detail.hit.zdb_id: 410466-3
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  • 5
    In: Nature Biotechnology, Springer Science and Business Media LLC
    Abstract: DNA comprises molecular information stored in genetic and epigenetic bases, both of which are vital to our understanding of biology. Most DNA sequencing approaches address either genetics or epigenetics and thus capture incomplete information. Methods widely used to detect epigenetic DNA bases fail to capture common C-to-T mutations or distinguish 5-methylcytosine from 5-hydroxymethylcytosine. We present a single base-resolution sequencing methodology that sequences complete genetics and the two most common cytosine modifications in a single workflow. DNA is copied and bases are enzymatically converted. Coupled decoding of bases across the original and copy strand provides a phased digital readout. Methods are demonstrated on human genomic DNA and cell-free DNA from a blood sample of a patient with cancer. The approach is accurate, requires low DNA input and has a simple workflow and analysis pipeline. Simultaneous, phased reading of genetic and epigenetic bases provides a more complete picture of the information stored in genomes and has applications throughout biomedicine.
    Type of Medium: Online Resource
    ISSN: 1087-0156 , 1546-1696
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
    detail.hit.zdb_id: 1494943-X
    detail.hit.zdb_id: 1311932-1
    SSG: 12
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  • 6
    Online Resource
    Online Resource
    Society for Industrial & Applied Mathematics (SIAM) ; 2013
    In:  SIAM Journal on Computing Vol. 42, No. 5 ( 2013-01), p. 1915-1939
    In: SIAM Journal on Computing, Society for Industrial & Applied Mathematics (SIAM), Vol. 42, No. 5 ( 2013-01), p. 1915-1939
    Type of Medium: Online Resource
    ISSN: 0097-5397 , 1095-7111
    RVK:
    Language: English
    Publisher: Society for Industrial & Applied Mathematics (SIAM)
    Publication Date: 2013
    detail.hit.zdb_id: 1383550-6
    detail.hit.zdb_id: 185851-8
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  • 7
    Online Resource
    Online Resource
    Springer Science and Business Media LLC ; 2022
    In:  BMC Medical Informatics and Decision Making Vol. 22, No. 1 ( 2022-12-07)
    In: BMC Medical Informatics and Decision Making, Springer Science and Business Media LLC, Vol. 22, No. 1 ( 2022-12-07)
    Abstract: Models that can effectively represent structured Electronic Healthcare Records (EHR) are central to an increasing range of applications in healthcare. Due to the sequential nature of health data, Recurrent Neural Networks have emerged as the dominant component within state-of-the-art architectures. The signature transform represents an alternative modelling paradigm for sequential data. This transform provides a non-learnt approach to creating a fixed vector representation of temporal features and has shown strong performances across an increasing number of domains, including medical data. However, the signature method has not yet been applied to structured EHR data. To this end, we follow recent work that enables the signature to be used as a differentiable layer within a neural architecture enabling application in high dimensional domains where calculation would have previously been intractable. Using a heart failure prediction task as an exemplar, we provide an empirical evaluation of different variations of the signature method and compare against state-of-the-art baselines. This first application of neural-signature methods in real-world healthcare data shows a competitive performance when compared to strong baselines and thus warrants further investigation within the health domain.
    Type of Medium: Online Resource
    ISSN: 1472-6947
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
    detail.hit.zdb_id: 2046490-3
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  • 8
    Online Resource
    Online Resource
    The Electronic Journal of Combinatorics ; 2013
    In:  The Electronic Journal of Combinatorics Vol. 20, No. 3 ( 2013-08-09)
    In: The Electronic Journal of Combinatorics, The Electronic Journal of Combinatorics, Vol. 20, No. 3 ( 2013-08-09)
    Abstract: In this paper we obtain the expectation and variance of the number of Euler tours of a random Eulerian directed graph with fixed out-degree sequence. We use this to obtain the asymptotic distribution of the number of Euler tours of a random $d$-in/$d$-out graph and prove a concentration result. We are then able to show that a very simple approach for uniform sampling or approximately counting Euler tours yields algorithms running in expected polynomial time for almost every $d$-in/$d$-out graph. We make use of the BEST theorem of de Bruijn, van Aardenne-Ehrenfest, Smith and Tutte, which shows that the number of Euler tours of an Eulerian directed graph with out-degree sequence $\mathbf{d}$ is the product of the number of arborescences and the term $\frac{1}{|V|}[\prod_{v\in V}(d_v-1)!]$. Therefore most of our effort is towards estimating the moments of the number of arborescences of a random graph with fixed out-degree sequence.
    Type of Medium: Online Resource
    ISSN: 1077-8926
    Language: Unknown
    Publisher: The Electronic Journal of Combinatorics
    Publication Date: 2013
    detail.hit.zdb_id: 2010998-2
    SSG: 17,1
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