| Papers, etc. |
Note on Electronic Access to Journals
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.
03/26: ---- Organizational Meeting ----
04/02: Peptide retention time prediction yields
improved tandem mass spectrum identification for diverse
chromatography conditions -- Aaron Klammer
04/09: Prediction of tissue-specific cis-regulatory
modules using Bayesian networks and regression trees -- Xiaoyu Chen
- M Blanchette, AR Bataille, X Chen, C Poitras, J Laganière, C Lefèbvre, G Deblois, V Giguère, V Ferretti, D Bergeron, B Coulombe, F Robert, "Genome-wide computational prediction of transcriptional regulatory modules reveals new insights into human gene expression." Genome Res., 16, #5 (2006) 656-68.
[offcampus]
04/16: Algorithms for combining rooted triplets into
a galled phylogenetic network -- Nguyen Nguyen
Jesper Jansson, Nguyen Bao Nguyen, and Wing-Kin Sung,
SIAM Journal on Computing, Volume 35 Issue 5, Pages 1098-1121
(2006).
Abstract:
This paper considers the problem of determining whether a given set
T of rooted triplets can be merged without conflicts into a
galled phylogenetic network and, if so, constructing such a
network. When the input T is dense, we solve the problem in
O(|T|) time, which is optimal since the size of the input is
Theta(|T|). In comparison, the previously fastest algorithm
for this problem runs in O(|T|2) time. We also develop an
optimal O(|T|)-time algorithm for enumerating all simple
phylogenetic networks leaf-labeled by L that are consistent
with T, where L is the set of leaf labels in T, which is
used by our main algorithm. Next, we prove that the problem
becomes NP-hard if extended to nondense inputs, even for the
special case of simple phylogenetic networks. We also show that
for every positive integer n, there exists some set T of
rooted triplets on n leaves such that any galled network can
be consistent with at most 0.4883 * |T| of the rooted
triplets in T. On the other hand, we provide a
polynomial-time approximation algorithm that always outputs a
galled network consistent with at least a factor of
5/12 (> 0.41) of the rooted triplets in T.
04/23: A computational pipeline for high throughput
discovery of cis-regulatory noncoding RNA in prokaryotes -- Zizhen Yao
Abstract:
Noncoding RNAs (ncRNAs) are important functional RNAs that do
not code for proteins. We present a highly efficient
computational pipeline for discovering cis-regulatory ncRNA
motifs de novo. The pipeline differs from previous methods in
that it is structure-oriented, does not require a multiple
sequence alignment as input, and is capable of detecting RNA
motifs with low sequence conservation. We also integrate RNA
motif prediction with RNA homolog search, which improves the
quality of the RNA motifs significantly. Here we report the
results of applying this pipeline to Firmicute bacteria. Our top
ranking motifs include most known Firmicute Rfam families.
Comparing our motif models with Rfam's hand-curated motif
models, we achieve high accuracy in both membership prediction
and base-pair-level secondary structure prediction (at least 75%
average sensitivity and specificity on both tasks). Of the ncRNA
candidates not in Rfam, we find compelling evidence that some of
them are functional, and analyze several potential ribosomal
protein leaders in depth.
Joint work with Jeffrey Barrick, Zasha Weinberg, Shane
Neph, Ronald Breaker, Martin Tompa and Walter L. Ruzzo
04/30: T1DBase: integration and presentation of
complex data for type 1 diabetes research. -- Karen Friery, ISB
- EM Hulbert, LJ Smink, EC Adlem, JE Allen, DB Burdick, OS Burren, CC Cavnor, GE Dolman, D Flamez, KF Friery, BC Healy, SA Killcoyne, B Kutlu, H Schuilenburg, NM Walker, J Mychaleckyj, DL Eizirik, LS Wicker, JA Todd, N Goodman, "T1DBase: integration and presentation of complex data for type 1 diabetes research." Nucleic Acids Res., 35, #Database issue (2007) D742-6.
[offcampus]
Abstract:
T1DBase (http://T1DBase.org) [Smink et al. (2005) Nucleic Acids
Res., 33, D544-D549; Burren et al. (2004) Hum. Genomics, 1,
98-109] is a public website and database that supports the type
1 diabetes (T1D) research community. T1DBase provides a
consolidated T1D-oriented view of the complex data world that
now confronts medical researchers and enables scientists to
navigate from information they know to information that is new
to them. Overview pages for genes and markers summarize
information for these elements. The Gene Dossier summarizes
information for a list of genes. GBrowse [Stein et al. (2002)
Genome Res., 10, 1599-1610] displays genes and other features in
their genomic context, and Cytoscape [Shannon et al. (2003)
Genome Res., 13, 2498-2504] shows genes in the context of
interacting proteins and genes. The Beta Cell Gene Atlas shows
gene expression in beta cells, islets, and related cell types
and lines, and the Tissue Expression Viewer shows expression
across other tissues. The Microarray Viewer shows expression
from more than 20 array experiments. The Beta Cell Gene
Expression Bank contains manually curated gene and pathway
annotations for genes expressed in beta cells. T1DMart is a
query tool for markers and genotypes. PosterPages are 'home
pages' about specific topics or datasets. The key challenge, now
and in the future, is to provide powerful informatics
capabilities to T1D scientists in a form they can use to enhance
their research.
05/07: Estimation of recombination rate heterogeneity using full
likelihood method.
-- Chul Joo Kang, GS
Abstract:
Current studies showed that recombination rate on human genome
is not equally distributed. Some regions (recombination hotspot)
have much higher recombination rate compare to rest of genome.
There are some methods to estimate the variations in
recombination rate using approximation of likelihood. I want to
talk about method using the full likelihood approaches to
estimate these variations of recombination rate.
Background readings:
05/14: Join us all day in room CSE 691, especially for the keynote at
3:30:
Dr. Steve Henikoff, FHCRC, ``Epigenomic profiling to
study histone dynamics''
-- Special Event:
CMB Student Symposium
05/21: A computational method to improve gene expression -- Harlan Robins, FHCRC
Background reading:
- R Schneider, M Campbell, G Nasioulas, BK Felber, GN Pavlakis, "Inactivation of the human immunodeficiency virus type 1 inhibitory elements allows Rev-independent expression of Gag and Gag/protease and particle formation." J. Virol., 71, #7 (1997) 4892-903.
[offcampus]
- SL Harris, G Gil, H Robins, W Hu, K Hirshfield, E Bond, G Bond, AJ Levine, "Detection of functional single-nucleotide polymorphisms that affect apoptosis." Proc. Natl. Acad. Sci. U.S.A., 102, #45 (2005) 16297-302.
[offcampus]
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