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CSE 590C, Wi '11: Reading & Research in Comp. Bio. |
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| Course Info |
CSE 590C is a weekly seminar on Readings and Research in
Computational Biology, open to all graduate students in computational,
biological, and mathematical sciences.
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| Schedule |
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| Papers, etc. |
Links to full papers below are often to journals that require a
paid subscription. The UW Library is generally a paid
subscriber, and you can freely access these articles if you do
so from an on-campus computer. For off-campus access,
follow the "[offcampus]" links below or
look at the
library "proxy server" instructions.
You will be prompted for your UW net ID and password once per
session.
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| Abstract: The human microbiome is the collection of microorganisms
which live inside and on us; recent studies have established the
centrality of the microbiome to human health. These studies raise a
number of questions: Given a collection of samples from a single
body location, which samples indicate a healthy versus unhealthy
phenotype? Do these samples fall into natural "types" from which
one can generalize? What are the "units" of microbial communities,
and what are the significant synergistic and antagonistic
interactions between microbes?
High-throughput sequencing technologies have opened the door to understanding these questions via sequencing of genetic material extracted in bulk from a collection of microorganisms. Statistical methods can be used to assign these fragmentary sequences to locations on a "reference" phylogenetic tree using information about the genomes of previously identified species; each sample thus results in a cloud of points on the reference tree. One can approach the above questions by developing statistical methods for comparing such clouds. From a probabilistic perspective, an appropriate comparative tool is the classical Kantorovich-Rubinstein metric (a.k.a. "earth-mover's distance"), which we have shown is a generalization of the "UniFrac" metric popularized in 2005 by microbial ecologists. One can define related clustering and ordination techniques which operate directly on the underlying clouds of points, rather than solely on a matrix of distances derived from the clouds. I will describe this theoretical work, as well as my OCaml software implementation, in the context of our project researching the microbiome of the human vagina. This is joint work with Steve Evans (UC Berkeley), Robin Kodner (UW), Ginger Armbrust (UW), Noah Hoffman (UW), David Fredricks (FHCRC), Sujatha Srinivasan (FHCRC), and Martin Morgan (FHCRC). See the first two papers on http://matsen.fhcrc.org/papers.html. The third is also relevant. |
01/17: -- Holiday
01/24: von Neuman rejection sampling -- Miles; Felsenstein
01/31: Evolvability in metabolic networks -- Brandon; Borenstein
02/07: dsRNA in Arabidopsis -- Rita, Elizabeth; Ruzzo
02/14: Conservation of nucleosome positioning -- Benjamin; Noble
02/21: -- Holiday
02/28: Coevolution in a transcriptional network -- James, Kris; Tompa
03/07: ModENCODE analysis of C. elegans -- Daniel; Bolouri
CSE's Computational Molecular Biology research group
Interdisciplinary Ph.D. program in Computational Molecular Biology
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Computer Science & Engineering University of Washington Box 352350 Seattle, WA 98195-2350 (206) 543-1695 voice, (206) 543-2969 FAX |
Note on Electronic Access to Journals