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[nl-uiuc] AIIS Reminder - Today @ 2pm - Machine Reading for Cancer Panomics


Chronological Thread 
  • From: Yonatan Bisk <bisk1 AT illinois.edu>
  • To: nl-uiuc <nl-uiuc AT cs.uiuc.edu>, AIVR <aivr AT cs.uiuc.edu>, Vision List <vision AT cs.uiuc.edu>, aiis AT cs.uiuc.edu, aistudents AT cs.uiuc.edu, "Girju, Corina R" <girju AT illinois.edu>, Catherine Blake <clblake AT illinois.edu>, "Efron, Miles James" <mefron AT illinois.edu>, "Lee, Soo Min" <lee203 AT illinois.edu>, Jana Diesner <jdiesner AT illinois.edu>, "Raginsky, Maxim" <maxim AT illinois.edu>, "Sinha, Saurabh" <sinhas AT illinois.edu>
  • Subject: [nl-uiuc] AIIS Reminder - Today @ 2pm - Machine Reading for Cancer Panomics
  • Date: Fri, 24 Jan 2014 10:57:02 -0600
  • List-archive: <http://lists.cs.uiuc.edu/pipermail/nl-uiuc/>
  • List-id: Natural language research announcements <nl-uiuc.cs.uiuc.edu>

When:     Today @ 2pm
Where:    3405 SC
Speaker: Hoifung Poon ( http://research.microsoft.com/en-us/um/people/hoifung/ )


Title: Machine Reading for Cancer Panomics
                               
Abstract: Advances in sequencing technology have made available a plethora of panomics data for cancer research, yet the search for disease genes and drug targets remains a formidable challenge. Biological knowledge such as pathways can play an important role by constraining the search space and boosting the signal-to-noise ratio. The majority of knowledge resides in text (e.g., journal publications), which has been undergoing its own exponential growth, making it mandatory to develop machine reading methods for automatic knowledge extraction. In this talk, I will formulate the machine reading task for pathway extraction, review the state of the art and open challenges, and present our Literome project and latest attack to the problem using grounded unsupervised semantic parsing.
                               
Bio: Hoifung Poon is a researcher at Microsoft Research. His research interests are in advancing machine learning and natural language processing (NLP) to help automate discovery in genomics and precision medicine. His most recent work focuses on scaling semantic parsing to Pubmed for extracting biological pathways, and on developing probabilistic methods to incorporate pathways with high-throughput omics data in cancer systems biology. He has received Best Paper Awards in premier NLP and machine learning venues such as the Conference of the North American Chapter of the Association for Computational Linguistics, the Conference of Empirical Methods in Natural Language Processing, and the Conference of Uncertainty in AI.


  • [nl-uiuc] AIIS Reminder - Today @ 2pm - Machine Reading for Cancer Panomics, Yonatan Bisk, 01/24/2014

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