[gov3009-l] Applied Statistics Workshop: John Quackenbush on Wed., February 1

Konstantin Kashin kkashin at fas.harvard.edu
Mon Jan 30 02:39:28 EST 2012

Dear all,

Please join us for the Applied Statistics Workshop (Gov 3009) this
Wednesday, February 1 from 12.00 - 1.30 pm in CGIS Knafel Room 354. John
of Biostatistics and Computational Biology and Director of the
Center for Cancer Computational Biology at the Dana-Farber Cancer
Institute, will give a presentation entitled "Moving Beyond the Mean: The
Role of Variation in Determining Phenotype". As always, a light lunch will
be provided.


*Two trends are driving innovation and discovery in biological sciences:
technologies that allow holistic surveys of genes, proteins, and
metabolites and a realization that biological processes are driven by
complex networks of interacting biological molecules. However, there is a
gap between the gene lists emerging from genome sequencing projects and the
network diagrams that are essential if we are to understand the link
between genotype and phenotype. 'Omic technologies were once heralded as
providing a window into those networks, but so far their success has been
limited, in large part because the high-dimensional they produce cannot be
fully constrained by the limited number of measurements and in part because
the data themselves represent only a small part of the complete story. To
circumvent these limitations, we have developed methods that combine 'omic
data with other sources of information in an effort to leverage, more
completely, the compendium of information that we have been able to amass.
Here we will present a number of approaches we have developed, with an
emphasis on the how those methods have provided into the role that
particular cellular pathways play in driving differentiation, and the role
that variation in gene expression patterns influences the development of
disease states. In particular, we will challenge the basic analytical that
have been used in biomedical research and argue that one should move beyond
a simple comparison of the means relative to variance (the t-test) but
instead also consider how variance itself changes between phenotypes.
Looking forward, we will examine more abstract state-space models that may
have potential to lead us to a more general predictive, theoretical biology.

An up-to-date schedule for the workshop is available at


Konstantin Kashin
Ph.D. Student in Government
Harvard University

Mobile: 978-844-0538
E-mail: kkashin at fas.harvard.edu
Site: http://people.fas.harvard.edu/~kkashin/
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