Search Results - "Budden, David"

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  1. 1

    A Global Social Media Survey of Attitudes to Human Genome Editing by McCaughey, Tristan, Sanfilippo, Paul G., Gooden, George E.C., Budden, David M., Fan, Li, Fenwick, Eva, Rees, Gwyneth, MacGregor, Casimir, Si, Lei, Chen, Christine, Liang, Helena Hai, Baldwin, Timothy, Pébay, Alice, Hewitt, Alex W.

    Published in Cell stem cell (05-05-2016)
    “…Ongoing breakthroughs with CRISPR/Cas-based editing could potentially revolutionize modern medicine, but there are many questions to resolve about the ethical…”
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    Journal Article
  2. 2

    A Need for Better Understanding Is the Major Determinant for Public Perceptions of Human Gene Editing by McCaughey, Tristan, Budden, David M, Sanfilippo, Paul G, Gooden, George E C, Fan, Li, Fenwick, Eva, Rees, Gwyneth, MacGregor, Casimir, Si, Lei, Chen, Christine, Liang, Helena Hai, Pébay, Alice, Baldwin, Timothy, Hewitt, Alex W

    Published in Human gene therapy (01-01-2019)
    “…The CRISPR/Cas system could provide an efficient and reliable means of editing the human genome and has the potential to revolutionize modern medicine;…”
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    Journal Article
  3. 3

    Information theoretic approaches for inference of biological networks from continuous-valued data by Budden, David M, Crampin, Edmund J

    Published in BMC systems biology (06-09-2016)
    “…Characterising programs of gene regulation by studying individual protein-DNA and protein-protein interactions would require a large volume of high-resolution…”
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    Journal Article
  4. 4

    Distributed gene expression modelling for exploring variability in epigenetic function by Budden, David M, Crampin, Edmund J

    Published in BMC bioinformatics (05-11-2016)
    “…Predictive gene expression modelling is an important tool in computational biology due to the volume of high-throughput sequencing data generated by recent…”
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    Journal Article
  5. 5

    Predictive modelling of gene expression from transcriptional regulatory elements by Budden, David M, Hurley, Daniel G, Crampin, Edmund J

    Published in Briefings in bioinformatics (01-07-2015)
    “…Predictive modelling of gene expression provides a powerful framework for exploring the regulatory logic underpinning transcriptional regulation. Recent…”
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    Journal Article
  6. 6

    Addressing the non-functional requirements of computer vision systems: a case study by Fenn, Shannon, Mendes, Alexandre, Budden, David M.

    Published in Machine vision and applications (01-01-2016)
    “…Computer vision plays a major role in most autonomous systems and is particularly fundamental within the robotics industry, where vision data are the main…”
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    Journal Article
  7. 7

    Language Individuation and Marker Words: Shakespeare and His Maxwell's Demon by Marsden, John, Budden, David, Craig, Hugh, Moscato, Pablo

    Published in PloS one (27-06-2013)
    “…Within the structural and grammatical bounds of a common language, all authors develop their own distinctive writing styles. Whether the relative occurrence of…”
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    Journal Article
  8. 8

    Virtual Reference Environments: a simple way to make research reproducible by Hurley, Daniel G, Budden, David M, Crampin, Edmund J

    Published in Briefings in bioinformatics (01-09-2015)
    “…'Reproducible research' has received increasing attention over the past few years as bioinformatics and computational biology methodologies become more…”
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  9. 9

    RoboCup Simulation Leagues: Enabling Replicable and Robust Investigation of Complex Robotic Systems by Budden, David M., Wang, Peter, Obst, Oliver, Prokopenko, Mikhail

    Published in IEEE robotics & automation magazine (01-09-2015)
    “…Physically realistic simulated environments are powerful platforms for enabling measurable, replicable, and statistically robust investigation of complex…”
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    Journal Article
  10. 10

    Predicting expression: the complementary power of histone modification and transcription factor binding data by Budden, David M, Hurley, Daniel G, Cursons, Joseph, Markham, John F, Davis, Melissa J, Crampin, Edmund J

    Published in Epigenetics & chromatin (24-11-2014)
    “…Transcription factors (TFs) and histone modifications (HMs) play critical roles in gene expression by regulating mRNA transcription. Modelling frameworks have…”
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    Journal Article
  11. 11

    FlexDM: Simple, parallel and fault-tolerant data mining using WEKA by Flannery, Madison, Budden, David M, Mendes, Alexandre

    Published in Source code for biology and medicine (17-11-2015)
    “…With the continued exponential growth in data volume, large-scale data mining and machine learning experiments have become a necessity for many researchers…”
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    Journal Article
  12. 12

    NAIL, a software toolset for inferring, analyzing and visualizing regulatory networks by Hurley, Daniel G, Cursons, Joseph, Wang, Yi Kan, Budden, David M, Print, Cristin G, Crampin, Edmund J

    Published in Bioinformatics (Oxford, England) (15-01-2015)
    “…The wide variety of published approaches for the problem of regulatory network inference makes using multiple inference algorithms complex and time-consuming…”
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  13. 13
  14. 14

    Modelling the conditional regulatory activity of methylated and bivalent promoters by Budden, David M, Hurley, Daniel G, Crampin, Edmund J

    Published in Epigenetics & chromatin (19-06-2015)
    “…Predictive modelling of gene expression is a powerful framework for the in silico exploration of transcriptional regulatory interactions through the…”
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    Journal Article
  15. 15

    Cautionary Tales of Inapproximability by Budden, David, Jones, Mitchell

    Published in Journal of computational biology (01-03-2017)
    “…Modeling biology as classical problems in computer science allows researchers to leverage the wealth of theoretical advancements in this field. Despite…”
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    Journal Article
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  17. 17

    Generative Compression by Santurkar, Shibani, Budden, David, Shavit, Nir

    Published in 2018 Picture Coding Symposium (PCS) (01-06-2018)
    “…Traditional image and video compression algorithms rely on hand-crafted encoder/decoder pairs (codecs) that lack adaptability and are agnostic to the data…”
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    Conference Proceeding
  18. 18

    A Combinatorial Perspective on Transfer Learning by Wang, Jianan, Sezener, Eren, Budden, David, Hutter, Marcus, Veness, Joel

    Published 23-10-2020
    “…Human intelligence is characterized not only by the capacity to learn complex skills, but the ability to rapidly adapt and acquire new skills within an…”
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    Journal Article
  19. 19

    Online Learning in Contextual Bandits using Gated Linear Networks by Sezener, Eren, Hutter, Marcus, Budden, David, Wang, Jianan, Veness, Joel

    Published 21-02-2020
    “…We introduce a new and completely online contextual bandit algorithm called Gated Linear Contextual Bandits (GLCB). This algorithm is based on Gated Linear…”
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    Journal Article
  20. 20

    The CLRS Algorithmic Reasoning Benchmark by Veličković, Petar, Badia, Adrià Puigdomènech, Budden, David, Pascanu, Razvan, Banino, Andrea, Dashevskiy, Misha, Hadsell, Raia, Blundell, Charles

    Published 31-05-2022
    “…Learning representations of algorithms is an emerging area of machine learning, seeking to bridge concepts from neural networks with classical algorithms…”
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    Journal Article