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SUMMARY:Progress on development of a microfluidic robot scientist - Prof. 
 Stephen Muggleton\, Imperial College London
DTSTART:20090602T130000Z
DTEND:20090602T141000Z
UID:TALK17885@talks.cam.ac.uk
CONTACT:Dr Fabien Petitcolas
DESCRIPTION:*Abstract*: Synthetic Biology is an emerging discipline that i
 s providing a conceptual framework for engineering biological devices base
 d on the principles of standardisation\, modularity and abstraction.  To b
 ecome a widely applied engineering discipline it will be critical for the 
 newly designed biological devices to function in a robust and predictable 
 fashion.  This project is involved in the development of a microfluidic ro
 bot scientist that will address these limitations. We areintegrating compu
 tational hypotheses with automatic generation of experimental trials withi
 n a microfluidic device. The use of droplet microfluidics reduces reagent 
 volumes and increases throughput. The strategy maximises the efficiency of
  convergence to optimal values as applied to the engineering of proteins w
 ith new ligand binding specificities. This approach will enable the design
  and empirical testing of robust BioPart and device-level Synthetic Biolog
 y designs\, which will have general applicability. Specifically we will de
 sign novel ligand-binding for the LuxR family of bacterial quorum sensing 
 proteins to enable the rational engineering of orthogonal bacterial signal
 ling pathways. The project is being conducted as an interdisciplinary coll
 aboration between computing\, bioscience\, chemical and bio-engineering at
  Imperial College London as part of the work of the Institute of Systems a
 nd Synthetic Biology (IoSSB).\n\n*Biography*: Professor Stephen Muggleton 
 holds the a Royal Academy of Engineering and Microsoft Research Chair (200
 7-) and is Director of the Imperial College Computational Bioinformatics C
 entre (2001-) (www.doc.ic.ac.uk/bioinformatics) and Acting Director of for
  the Imperial College Centre for Integrated Systems Biology. Prof. Mugglet
 on's career has concentrated on the development of theory\, implementation
 s and applications of Machine Learning\, particularly in the field of Indu
 ctive Logic Programming.  Over the last decade he has collaborated increas
 ingly with biological colleagues\, in particular Prof Mike Sternberg\, on 
 applications of Machine Learning to Biological prediction tasks. These tas
 ks have included the determination of protein structure\, the activity of 
 drugs and toxins and the assignment of gene function.  Previous posts were
  as Professor of Machine Learning at the Computer Science Department\, Uni
 versity of York (1997-2001) \; Reader in Machine Learning and Research Fel
 low at Wolfson College Oxford (1993-1997)\; EPSRC Advanced Research Fellow
  (1993-1997)\; Visiting Associate Professor (Fujitsu Chair) at the Univers
 ity of Tokyo.  EPSRC Post-doctoral Fellow and Turing Institute Fellow (198
 7-1992)\; PhD in Artificial Intelligence Edinburgh University (1986)\; BSc
  in Computer Science Edinburgh University (1983). Professional positions: 
 Fellow of the American Association for Artificial Intelligence (2002-)\, E
 ditor-in-Chief of the Machine Intelligence series\; panel member for the D
 TI Functional Genomics inintiative (2002-2005) and the BBSRC EBI Committee
  (2004-2006).\n\n*Note*: This talk\, which is part of a series of 4 presen
 tations that afternoon\, will be preceded at 2pm by a brief introduction b
 y Rick Rashid\, Senior Vice President\, Microsoft Research.
LOCATION:Large public lecture room\, Microsoft Research\, Roger Needham Bu
 ilding\, 7 J J Thomson Avenue\, Cambridge CB3 0FB
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