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  • 1
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    Optimizing peer review of software code--response (2013)
    American Association for the Advancement of Science (AAAS)
    Details
    Publication Date: 2013-07-23
    Description: 〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Joppa, Lucas N -- Gavaghan, David -- Harper, Richard -- Takeda, Kenji -- Emmott, Stephen -- New York, N.Y. -- Science. 2013 Jul 19;341(6143):237. doi: 10.1126/science.341.6143.237-a.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/23869003" target="_blank"〉PubMed〈/a〉
    Keywords: Computer Simulation/*utilization ; Humans ; Research/*trends ; *Software
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
    Published by American Association for the Advancement of Science (AAAS)
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  • 2
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    Ecosystems: Time to model all life on Earth (2013)
    Nature Publishing Group (NPG)
    Details
    Publication Date: 2013-01-18
    Description: 〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Purves, Drew -- Scharlemann, Jorn -- Harfoot, Mike -- Newbold, Tim -- Tittensor, Derek P -- Hutton, Jon -- Emmott, Stephen -- England -- Nature. 2013 Jan 17;493(7432):295-7. doi: 10.1038/493295a.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Computational Ecology and Environmental Science Group at Microsoft Research in Cambridge, UK.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/23325192" target="_blank"〉PubMed〈/a〉
    Keywords: Animals ; Earth (Planet) ; Ecology/*methods ; *Ecosystem ; Life ; *Models, Biological
    Print ISSN: 0028-0836
    Electronic ISSN: 1476-4687
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
    Published by Nature Publishing Group (NPG)
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  • 3
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    Computational science. Troubling trends in scientific software use (2013)
    American Association for the Advancement of Science (AAAS)
    Details
    Publication Date: 2013-05-21
    Description: 〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Joppa, Lucas N -- McInerny, Greg -- Harper, Richard -- Salido, Lara -- Takeda, Kenji -- O'Hara, Kenton -- Gavaghan, David -- Emmott, Stephen -- New York, N.Y. -- Science. 2013 May 17;340(6134):814-5. doi: 10.1126/science.1231535.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Microsoft Research, Cambridge CB1 2FB, UK. lujoppa@microsoft.com〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/23687031" target="_blank"〉PubMed〈/a〉
    Keywords: Computer Simulation/*utilization ; Humans ; Research/*trends ; *Software
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
    Published by American Association for the Advancement of Science (AAAS)
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  • 4
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    Defining an essential transcription factor program for naive pluripotency (2014)
    American Association for the Advancement of Science (AAAS)
    Details
    Publication Date: 2014-06-07
    Description: The gene regulatory circuitry through which pluripotent embryonic stem (ES) cells choose between self-renewal and differentiation appears vast and has yet to be distilled into an executive molecular program. We developed a data-constrained, computational approach to reduce complexity and to derive a set of functionally validated components and interaction combinations sufficient to explain observed ES cell behavior. This minimal set, the simplest version of which comprises only 16 interactions, 12 components, and three inputs, satisfies all prior specifications for self-renewal and furthermore predicts unknown and nonintuitive responses to compound genetic perturbations with an overall accuracy of 70%. We propose that propagation of ES cell identity is not determined by a vast interactome but rather can be explained by a relatively simple process of molecular computation.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4257066/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4257066/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Dunn, S-J -- Martello, G -- Yordanov, B -- Emmott, S -- Smith, A G -- 091484/Wellcome Trust/United Kingdom -- G1100526/Medical Research Council/United Kingdom -- G19/38/Medical Research Council/United Kingdom -- MC_PC_12009/Medical Research Council/United Kingdom -- Medical Research Council/United Kingdom -- Wellcome Trust/United Kingdom -- New York, N.Y. -- Science. 2014 Jun 6;344(6188):1156-60. doi: 10.1126/science.1248882.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Computational Science Laboratory, Microsoft Research, Cambridge CB1 2FB, UK. ; Wellcome Trust-Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge CB2 1QR, UK. graziano.martello@unipd.it austin.smith@cscr.cam.ac.uk. ; Wellcome Trust-Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge CB2 1QR, UK. Department of Biochemistry, University of Cambridge, Cambridge, UK. graziano.martello@unipd.it austin.smith@cscr.cam.ac.uk.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/24904165" target="_blank"〉PubMed〈/a〉
    Keywords: Animals ; Cell Culture Techniques ; Computational Biology ; Embryonic Stem Cells/*metabolism ; *Gene Expression Regulation ; *Gene Regulatory Networks ; Mice ; Pluripotent Stem Cells/*metabolism ; Transcription Factors/genetics/*metabolism
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
    Published by American Association for the Advancement of Science (AAAS)
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  • 5
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    Efficient Biologically Inspired Photocell Enhanced by Delocalized Quantum States (2013)
    American Physical Society (APS)
    Details
    Publication Date: 2013-12-19
    Description: Author(s): C. Creatore, M. A. Parker, S. Emmott, and A. W. Chin Artificially implementing the biological light reactions responsible for the remarkably efficient photon-to-charge conversion in photosynthetic complexes represents a new direction for the future development of photovoltaic devices. Here, we develop such a paradigm and present a model photocell base... [Phys. Rev. Lett. 111, 253601] Published Wed Dec 18, 2013
    Keywords: Atomic, Molecular, and Optical Physics
    Print ISSN: 0031-9007
    Electronic ISSN: 1079-7114
    Topics: Physics
    Published by American Physical Society (APS)
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  • 6
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    Efficient Biologically Inspired Photocell Enhanced by Delocalized Quantum States (2013)
    American Physical Society
    Details
    Publication Date: 2013-12-18
    Print ISSN: 0031-9007
    Electronic ISSN: 1079-7114
    Topics: Physics
    Published by American Physical Society
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  • 7
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    Visual DSD: a design and analysis tool for DNA strand displacement systems (2011)
    Oxford University Press
    Details
    Publication Date: 2011-10-07
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
    Published by Oxford University Press
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  • 8
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    Optimizing Peer Review of Software Code--Response (2013)
    American Association for the Advancement of Science
    Details
    Publication Date: 2013-07-18
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
    Published by American Association for the Advancement of Science
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  • 9
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    The climate dependence of the terrestrial carbon cycle; including parameter and structural uncertainties (2012)
    Copernicus
    Details
    Publication Date: 2012-10-04
    Description: The feedback between climate and the terrestrial carbon cycle will be a key determinant of the dynamics of the Earth System over the coming decades and centuries. However Earth System Model projections of the terrestrial carbon-balance vary widely over these timescales. This is largely due to differences in their carbon cycle models. A major goal in biogeosciences is therefore to improve understanding of the terrestrial carbon cycle to enable better constrained projections. Essential to achieving this goal will be assessing the empirical support for alternative models of component processes, identifying key uncertainties and inconsistencies, and ultimately identifying the models that are most consistent with empirical evidence. To begin meeting these requirements we data-constrained all parameters of all component processes within a global terrestrial carbon model. Our goals were to assess the climate dependencies obtained for different component processes when all parameters have been inferred from empirical data, assess whether these were consistent with current knowledge and understanding, assess the importance of different data sets and the model structure for inferring those dependencies, assess the predictive accuracy of the model, and to identify a methodology by which alternative component models could be compared within the same framework in future. Although formulated as differential equations describing carbon fluxes through plant and soil pools, the model was fitted assuming the carbon pools were in states of dynamic equilibrium (input rates equal output rates). Thus, the parameterised model is of the equilibrium terrestrial carbon cycle. All but 2 of the 12 component processes to the model were inferred to have strong climate dependencies although it was not possible to data-constrain all parameters indicating some potentially redundant details. Similar climate dependencies were obtained for most processes whether inferred individually from their corresponding data sets or using the full terrestrial carbon model and all available data sets, indicating a strong overall consistency in the information provided by different data sets under the assumed model formulation. A notable exception was plant mortality, in which qualitatively different climate dependencies were inferred depending on the model formulation and data sets used, highlighting this component as the major structural uncertainty in the model. All but two component processes predicted empirical data better than a null model in which no climate dependency was assumed. Equilibrium plant carbon was predicted especially well (explaining around 70% of the variation in the withheld evaluation data). We discuss the advantages of our approach in relation to advancing our understanding of the carbon cycle and enabling Earth System Models make better constrained projections.
    Print ISSN: 1810-6277
    Electronic ISSN: 1810-6285
    Topics: Biology , Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 10
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    The climate dependence of the terrestrial carbon cycle, including parameter and structural uncertainties (2013)
    Copernicus
    Details
    Publication Date: 2013-01-29
    Description: The feedback between climate and the terrestrial carbon cycle will be a key determinant of the dynamics of the Earth System (the thin layer that contains and supports life) over the coming decades and centuries. However, Earth System Model projections of the terrestrial carbon-balance vary widely over these timescales. This is largely due to differences in their terrestrial carbon cycle models. A major goal in biogeosciences is therefore to improve understanding of the terrestrial carbon cycle to enable better constrained projections. Utilising empirical data to constrain and assess component processes in terrestrial carbon cycle models will be essential to achieving this goal. We used a new model construction method to data-constrain all parameters of all component processes within a global terrestrial carbon model, employing as data constraints a collection of 12 empirical data sets characterising global patterns of carbon stocks and flows. Our goals were to assess the climate dependencies inferred for all component processes, assess whether these were consistent with current knowledge and understanding, assess the importance of different data sets and the model structure for inferring those dependencies, assess the predictive accuracy of the model and ultimately to identify a methodology by which alternative component models could be compared within the same framework in the future. Although formulated as differential equations describing carbon fluxes through plant and soil pools, the model was fitted assuming the carbon pools were in states of dynamic equilibrium (input rates equal output rates). Thus, the parameterised model is of the equilibrium terrestrial carbon cycle. All but 2 of the 12 component processes to the model were inferred to have strong climate dependencies, although it was not possible to data-constrain all parameters, indicating some potentially redundant details. Similar climate dependencies were obtained for most processes, whether inferred individually from their corresponding data sets or using the full terrestrial carbon model and all available data sets, indicating a strong overall consistency in the information provided by different data sets under the assumed model formulation. A notable exception was plant mortality, in which qualitatively different climate dependencies were inferred depending on the model formulation and data sets used, highlighting this component as the major structural uncertainty in the model. All but two component processes predicted empirical data better than a null model in which no climate dependency was assumed. Equilibrium plant carbon was predicted especially well (explaining around 70% of the variation in the withheld evaluation data). We discuss the advantages of our approach in relation to advancing our understanding of the carbon cycle and enabling Earth System Models to make better constrained projections.
    Print ISSN: 1726-4170
    Electronic ISSN: 1726-4189
    Topics: Biology , Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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