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Luca Cardelli, Attila Csikasz-Nagy, Neil Dalchau, Mirco Tribastone, and Max Tschaikowski

Cells operate in noisy molecular environments via complex regulatory networks. It is possible to understand how molecular counts are related to noise in specific networks, but it is not generally clear how noise relates to network complexity, because different levels of complexity also imply different overall number of molecules. For a fixed function, does increased network complexity reduce noise, beyond the mere increase of overall molecular counts? If so, complexity could provide an advantage...

Publication details
Date: 31 January 2016
Type: Article
Publisher: Nature Publishing Group
Paul K Grant, Neil Dalchau, James R Brown, Fernan Federici, Timothy J Rudge, Boyan Yordanov, Om Patange, Andrew Phillips, and Jim Haseloff

Bidirectional intercellular signaling is an essential feature of multicellular organisms, and the engineering of complex biological systems will require multiple pathways for intercellular signalling with minimal crosstalk. Natural quorum-sensing systems provide components for cell communication, but their use is often constrained by signal crosstalk. We have established new orthogonal systems for cell-cell communication using acyl homoserine lactone signaling systems. Quantitative measurements in...

Publication details
Date: 26 January 2016
Type: Article
Number: 849
Yiqi Luo, Anders Ahlstrom, Steven D. Allison, Niels H. Batjes, Victor Brovkin, Nuno Carvalhais, Adrian Chappell, Philippe Ciais, Eric A. Davidson, Adien Finzi, Katerina Georgiou, Bertrand Guenet, Oleksandra Hararuk, Jennifer W. Harden, Yujie He, Francesca Hopkins, Lifen Jiang, Charlie Koven, Robert B. Jackson, Chris D. Jones, Mark J. Lara, Junyi Liang, A. David McGuire, William Parton, Changhui Peng, James T. Randerson, Alejandro Salazar, Carlos A. Sierra, Matthew J. Smith, Hanqin Tian, Katherine E. O. Todd-Brown, Margaret Torn, Kees Jan van Groenigen, Ying Ping Wang, Tristan O. West, Yaxing Wei, William R. Wieder, Jianyang Xia, Xia Xu, Xiaofeng Xu, and Tao Zhou

Soil carbon (C) is a critical component of Earth system models (ESMs) and its diverse representations are a major source of the large spread across models in the terrestrial C sink from the 3rd to 5th assessment reports of the Intergovernmental Panel on Climate Change (IPCC). Improving soil C projections is of a high priority for Earth system modeling in the future IPCC and other assessments. To achieve this goal, we suggest that (1) model structures should reflect real-world...

Publication details
Date: 17 December 2015
Type: Article
J. Meyerholt, S. Zaehle, and M. J. Smith

Including a terrestrial nitrogen (N) cycle in Earth system models has led to substantial attenuation of predicted biosphere-climate feedbacks. However, the magnitude of this attenuation remains uncertain. A particularly important, but highly uncertain process is biological nitrogen fixation (BNF), which is the largest natural input of N to land ecosystems globally. In order to quantify this uncertainty, and estimate likely effects on terrestrial biosphere dynamics, we applied six alternative...

Publication details
Date: 9 December 2015
Type: Article
Yiqi Luo, Zheng Shi, Lifen Jiang, Jianyang Xia, Ying Wang, Manoj Kc, Junyi Liang, Xingjie Lu, Shuli Niu, Anders Ahlstrom, Oleksandra Hararuk, Alan Hastings, Forrest Hoffman, Belinda E. Medlyn, Martin Rasmussen, Matthew J. Smith, Kathe E. Todd-Brown, and Yingping Wang

Terrestrial ecosystems have been estimated to absorb roughly 30% of anthropogenic CO2 emissions. Past studies have identified myriad drivers of terrestrial carbon storage changes, such as fire, climate change, and land use changes. Those drivers influence the carbon storage change via diverse mechanisms, which have not been unified into a general theory so as to identify what control the direction and rate of terrestrial carbon storage dynamics. Here we propose a theoretical framework to...

Publication details
Date: 5 November 2015
Type: Inproceeding
Publisher: American Geophysical Union
Alistair Bailey, Neil Dalchau, Rachel Carter, Stephen Emmott, Andrew Phillips, Jörn M. Werner, and Tim Elliott

The selection of peptides for presentation at the surface of most nucleated cells by major histocompatibility complex class I molecules (MHC I) is crucial to the immune response in vertebrates. However, the mechanisms of the rapid selection of high affinity peptides by MHC I from amongst thousands of mostly low affinity peptides are not well understood. We developed computational systems models encoding distinct mechanistic hypotheses for two molecules, HLA-B*44:02 (B*4402) and HLA-B*44:05 (B*4405),...

Publication details
Date: 20 October 2015
Type: Article
Publisher: Nature Publishing Group
S. Caldararu, D. W. Purves, and M. J. Smith

Leaf seasonality impacts a variety of important biological, chemical and physical Earth system processes, which makes it essential to represent leaf phenology in ecosystem and climate models. However, we are still lacking a general, robust parametrisation of phenology at global scales. In this study, we use a simple process-based model, which describes phenology as a strategy for carbon optimality, to test the effects of the common assumption in global modelling studies that plant species within the...

Publication details
Date: 19 October 2015
Type: Article
Matthew J. Smith, Drew W. Purves, Lucas N. Joppa, Stephen Emmott, Vassily Lyutsarev, Christopher Bishop, Paul I. Palmer, Ben Calderhead, and Mark Vanderwel

Considerable efforts to quantify different sources of variation in climate change projections (some might say uncertainty) have led to a welcome set of additional information on which to base confidence about what and how different futures might unfold and how different types of mediating efforts might affect the future. Quantifying the impacts of these different sources of variation on key climate change projection metrics should be used in part to guide future model development efforts. I will report...

Publication details
Date: 6 October 2015
Type: Inproceeding
Publisher: AGU
Matthew J. Smith, Sadia E. Ahmed, Drew W. Purves, Stephen Emmott, Lucas N. Joppa, Silvia Caldararu, Piero Visconti, and Tim Newbold

While the use of geospatial data to assist in decision making is becoming increasingly common, the use of geotemporal information: information that can be indexed by geographical space AND time, is much rarer. I will describe our scientific research and software development efforts intended to advance the availability and use of geotemporal information in general. I will show two recent examples of "stacking" geotemporal information to support land use decision making in the Brazilian Amazon and Kenya,...

Publication details
Date: 6 October 2015
Type: Inproceeding
Publisher: AGU
Johannes Meyerholt, Soenke Zaehle, and Matthew J. Smith

Including a land nitrogen (N) cycle in current Earth system models has led to substantial attenuation of predicted land-climate feedbacks, but the magnitude of this N effect remains highly uncertain. The current magnitude and global change responses of major land N cycle processes are still not well understood. Biological nitrogen fixation (BNF) is one particularly important process, being the largest natural land input of N. However, global terrestrial BNF rates are highly uncertain and models lack...

Publication details
Date: 6 October 2015
Type: Inproceeding
Publisher: AGU
Matthew J. Smith, Derek P. Tittensor, Vassily Lyutsarev, and Eugene Murphy

Analyses of satellite-derived chlorophyll data indicate that the phase of rapid phytoplankton population growth in the North Atlantic (the ‘spring bloom’) is actually initiated in the winter rather than the spring, contradicting Sverdrup’s Critical Depth Hypothesis. An alternative disturbance-recovery hypothesis (DRH) has been proposed to explain this discrepancy, in which the rapid deepening of the mixed layer reduces zooplankton grazing rates sufficiently to initiate the bloom. We use Bayesian...

Publication details
Date: 6 October 2015
Type: Article
Publisher: AGU Publishing
Timothy J. Rudge, James R. Brown, Fernan Federici, Neil Dalchau, Andrew Phillips, James W Ajioka, and Jim Haseloff

Publication details
Date: 5 October 2015
Type: Article
William R. Weider, Steven D. Allison, Eric A. Davidson, Katerina Georgiou, Oleksandra Hararuk, Yujie He, Francesca Hopkins, Matthew J. Smith, Benjamin Sulman, Katherine Todd-Brown, Ying-Ping Wang, Jianyang Xia, and Xiaofeng Xu

Microbes influence soil organic matter decomposition and the long-term stabilization of carbon (C) in soils. We contend that by revising the representation of microbial processes and their interactions with the physicochemical soil environment, Earth system models (ESMs) will make more realistic global C cycle projections. Explicit representation of microbial processes presents considerable challenges due to the scale at which these processes occur. Thus, applying microbial theory in ESMs requires a...

Publication details
Date: 1 October 2015
Type: Article
Publisher: AGU Publications
Y. P. Wang, J. Jiang, B. Chen-Charpentier, F. B. Agusto, B. Hastings, F. Hoffman, M. Rasmussen, M. J. Smith, K. Todd-Brown, Y. Wang, X. Xu, and Y. Q. Luo

A number of nonlinear microbial models of soil carbon decomposition have been developed. Some of them have been applied globally but have yet to be shown to realistically represent soil carbon dynamics in the field. Therefore a thorough analysis of their key differences will be very useful for the future development of these models. Here we compare two nonlinear microbial models of soil carbon decomposition: one is based on reverse Michaelis-Menten kinetics (model A) and the other on regular...

Publication details
Date: 7 September 2015
Type: Article
Yoli Shavit, Boyan Yordanov, Sara-Jane Dunn, Christoph M. Wintersteiger, Youssef Hamadi, and Hillel Kugler

A fundamental question in biology is how cells change into specific cell types with unique roles throughout development. This process can be viewed as a program prescribing the system dynamics, governed by a network of genetic interactions. Recent experimental evidence suggests that these networks are not fixed but rather change their topology as cells develop. Currently, there are limited tools for the construction and analysis of such self-modifying biological programs. We introduce Switching Gene...

Publication details
Date: 1 September 2015
Type: Inproceeding
Publisher: Springer
Scott Carr and Neil Pittman

Software engineering tools for Hardware Design Languages (HDL) lag behind traditional software development tools by decades. However as heterogeneous computing becomes more pervasive, productive programming in HDLs will become vital. To this end, we have developed gNOSIS a static analysis platform for Verilog HDL. In this project we have extended gNOSIS to support System Verilog. A good analogy is C is to C++ as Verilog is to System Verilog, that is System Verilog is a superset of Verilog with more...

Publication details
Date: 1 September 2015
Type: Technical report
Number: MSR-TR-2015-68
Young-Bum Kim, Karl Stratos, Ruhi Sarikaya, and Minwoo Jeong

In natural language understanding (NLU), a user utterance can be labeled differently depending on the domain or application (e.g., weather vs. calendar). Standard domain adaptation techniques are not directly applicable to take advantage of the existing annotations because they assume that the label set is invariant. We propose a solution based on label embeddings induced from canonical correlation analysis (CCA) that reduces the problem to a standard domain adaptation task and allows use of a number of...

Publication details
Date: 29 August 2015
Type: Proceedings
Publisher: ACL – Association for Computational Linguistics
Young-Bum Kim, Karl Stratos, and Ruhi Sarikaya

In this paper, we apply the concept of pre-training to hidden-unit conditional random
fields (HUCRFs) to enable learning on unlabeled data. We present a simple yet effective pre-training technique that learns to associate words with their clusters, which are obtained in an unsupervised manner. The learned parameters are then used to initialize the supervised learning process. We also propose a word clustering technique based on canonical correlation analysis (CCA) that is sensitive to multiple word...

Publication details
Date: 28 August 2015
Type: Proceedings
Publisher: ACL – Association for Computational Linguistics
Young-Bum Kim, Karl Stratos, Xiaohu Liu, and Ruhi Sarikaya

In this paper, we introduce the task of selecting compact lexicon from large, noisy gazetteers.
This scenario arises often in practice, in particular spoken language understanding (SLU).
We propose a simple and effective solution based on matrix decomposition techniques:
canonical correlation analysis (CCA) and rank-revealing QR (RRQR) factorization. CCA is first used to derive low-dimensional gazetteer embeddings from domain-specific search logs. Then RRQR is used to find a subset of...

Publication details
Date: 27 August 2015
Type: Proceedings
Publisher: ACL – Association for Computational Linguistics
Neil Dalchau, Niall Murphy, Rasmus Petersen, and Boyan Yordanov

We consider how to generate chemical reaction networks (CRNs) from functional specifications. We propose a two-stage approach that combines synthesis by satisfiability modulo theories and Markov chain Monte Carlo based optimisation. First, we identify candidate CRNs that have the possibility to produce correct computations for a given finite set of inputs. We then optimise the reaction rates of each CRN using a combination of stochastic search techniques applied to the chemical master equation,...

Publication details
Date: 1 August 2015
Type: Article
Publisher: Springer
Dan Alistarh and Rati Gelashvili

Population protocols are networks of finite-state agents, interacting randomly, and updating their state using simple rules. Despite their extreme simplicity, these systems have been shown to cooperatively perform complex computational tasks, such as simulating register machines to compute standard arithmetic functions. The election of a unique leader agent is a key requirement in such computational constructions. Yet, the fastest currently known population protocol for electing a leader only...

Publication details
Date: 1 July 2015
Type: Inproceeding
Publisher: Springer
Rasmus Petersen, Matthew R. Lakin, and Andrew Phillips

DNA nanotechnology is a promising approach for engineering computation at the nanoscale, with potential applications in biofabrication and intelligent nanomedicine. DNA strand displacement is a general strategy for implementing a broad range of nanoscale computations, including any computation that can be expressed as a chemical reaction network. Modelling and analysis of DNA strand displacement systems is an important part of the design process, prior to experimental realisation. As experimental...

Publication details
Date: 1 July 2015
Type: Article
Publisher: In press
Jelte Mense, Paul I. Palmer, and Matthew J. Smith

Western Europe has experienced several large riots over the last decade (2005-2015), such as the Paris riots in 2005, the London riots in 2011 and the Stockholm riots in 2013. Such acts of civil violence generally lead to big social and economic costs. Being able to quantitatively describe riots can aid current understanding of the underlying mechanisms, and potentially help to identify and mitigate risks associated with these events. We describe a general agent-based model of riots and demonstrate how...

Publication details
Date: 9 June 2015
Type: Proceedings
Publisher: Springer
Neil Dalchau, Harish Chandran, Nikhil Gopalkrishnan, Andrew Phillips, and John Reif

Molecular devices made of nucleic acids can perform complex information processing tasks at the nanoscale, with potential applications in biofabrication and smart therapeutics. However, limitations in the speed and scalability of such devices in a well-mixed setting can significantly affect their performance. In this paper, we propose designs for localized circuits involving DNA molecules that are arranged on addressable substrates and interact via hybridization reactions. We propose designs for...

Publication details
Date: 1 June 2015
Type: Article
Publisher: American Chemical Society
Matthew R. Lakin, Darko Stefanovic, and Andrew Phillips

Chemical reaction networks are a powerful means of specifying the intended behaviour of synthetic biochemical systems. A high-level formal specification, expressed as a chemical reaction network, may be compiled into a lower-level encoding, which can be directly implemented in wet chemistry and may itself be expressed as a chemical reaction network. Here we present conditions under which a lower-level encoding correctly emulates the sequential dynamics of a high-level chemical reaction network. We...

Publication details
Date: 1 June 2015
Type: Article
Publisher: In press
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