[Colloquium] Seminar Announcement: Expert Opinions in Cancer Metastasis: Uncertainty, Discrepancies, Range and Models-TODAY!

[Ninfa Mayorga]

Computation Institute- Data Lunch Seminar (DLS)

Speaker: Anna Divoli, Postdoctoral Scholar, Department of Medicine,  
Institute for Genomics and Systems Biology
Date: March 18, 2011
Time: 12:00 PM - 1:00 PM
Location: The University of Chicago, Searle 240A, 5735 S. Ellis Avenue

Expert Opinions in Cancer Metastasis: Uncertainty, Discrepancies,  
Range and Models

Abstract:
Research in computational biology is often contingent on principal  
notions. Mathematical modeling is relying on valid initial  
assumptions. Text mining algorithms can only retrieve or extract  
information found in text. Knowledge representation requires a degree  
of knowledge consensus. Our understanding of certain areas in biology,  
however, is still in its infancy having a ripple effect in  
computational efforts.

In this talk I discuss a study on cancer metastasis - a complex  
biological phenomenon with vast clinical importance. Individual  
viewpoints from 28 experts in clinical or molecular aspects of cancer  
metastasis were harvested and summarized computationally. Detailed  
analysis of the data reveals areas of disagreement and a range of  
opinions on underlying causes and processes in metastasis. The  
language that experts used while communicating their views was also  
examined. The experts use gripping metaphors and much hedging.  
Extensive automatic analysis reveals high use of language associated  
with cognitive processes (certainty and insight, in particular) -  
language commonly under-represented in scientific text. The results  
from this study show that in reality knowledge is not as crisp as the  
view one might obtain by looking at textbooks and the scientific  
literature. There is speculation, uncertainty and difference of opinion.

These findings have ramifications in (i) building mathematical models  
of biological processes such as cancer metastasis, and (ii) formally  
representing metastasis. I propose probabilistic models and ontologies  
that systematically factor experts' hunches and speculations. I will  
also discuss the repercussions of this difference of opinion in  
scientific paper and grant reviewing.

Bio:
Anna is a postdoctoral scholar in Andrey Rzhetsky's group. Prior  
coming to Chicago, she completed her PhD in biomedical text mining at  
the University of Manchester and carried out postdoctoral research in  
biomedical user search interfaces in the School of Information at the  
University of California, Berkeley. Her research focuses on developing  
methodologies for acquiring biomedical knowledge from textual data and  
studying the effect of human factors in that process.
http://www.ci.uchicago.edu/~divoli/

Information: Lunch will be provided


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