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- Distribution Modeller: Environmental Modelling at the Speed of ThoughtDistribution Modeller (temporary name only!) is CEES' end-to-end browser tool that lets the researcher to rapidly import data, supplement that data with environmental info from FetchClimate, specify an arbitrary model by point and click or in code, parameterize the model against the data using Filzbach, make and visualize predictions with a full propagation of parameter uncertainty – then package and share everytihng, in a way that is inspectable, repeatable, and modifiable.
- ViralSearchIdentifying and Visualizing Viral Content
- SNAP Sequence AlignerSNAP is a new sequence aligner that is 10-100x faster and simultaneously more accurate than existing tools like BWA, Bowtie2 and SOAP2. It runs on commodity x86 processors, and supports a rich error model that lets it cheaply match reads with more differences from the reference than other tools. SNAP was developed by a team from the UC Berkeley AMP Lab, Microsoft, and UCSF. Binaries are available at http://github.com/downloads/amplab/snap/
- 2020 ScienceThe University College London and University of Oxford have recently received funding from the EPSRC Cross-Disciplinary Interfaces Programme (2020 Science: Mathematical and Computational Modelling of Complex Natural Systems) to collaborate with Microsoft Research Cambridge on a programme of research that will involve up to 17 post-doctoral Research Associates over a five year period.
Boyan Yordanov, Christoph Wintersteiger, Youssef Hamadi, Andrew Phillips, and Hillel Kugler, Functional Analysis of Large-scale DNA Strand Displacement Circuits, in DNA 19, Springer, September 2013
Wen Wang, Andreas Stolcke, Jiahong Yuan, and Mark Liberman, A Cross-language Study on Automatic Speech Disfluency Detection, in Proc. NAACL, Association for Computational Linguistics, June 2013
Gian Marco Palamara, Gustav W. Delius, Matthew J. Smith, and Owen L. Petchey, Predation effects on mean time to extinction under demographic stochasticity, in Journal of Theoretical Biology, Elsevier, June 2013
Zhipeng Gui, Chaowei Yang, Jizhe Xia, Jing Li, Abdelmounaam Rezgui, Min Sun, Yan Xu, and Daniel Fay, A visualization-enhanced graphical user interface for geospatial resource discovery, in Annals of GIS, vol. 0, no. 0, pp. 1-13, Taylor & Francis, 23 April 2013
Cory Merow, John A. Silander, and Matthew J. Smith, A practical guide to MaxEnt for modeling species' distributions: what it does, and why inputs and settings matter, in Ecography, Wiley, April 2013
