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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: Humans differ in many "phenotypes" such as weight, hair color and more importantly disease susceptibility. These phenotypes are largely determined by each individual's specific genotype, stored in the 3.2 billion bases of his or her genome sequence. Deciphering the sequence by finding which sequence variations cause a certain phenotype would have a great impact. The recent advent of high-throughput genotyping methods has enabled retrieval of an individual's sequence information on a genome-wide scale. Classical approaches have focused on identifying which sequence variations are associated with a particular phenotype. However, the complexity of cellular mechanisms, through which sequence variations cause a particular phenotype, makes it difficult to directly infer such causal relationships. In this talk, I will present machine learning approaches that address these challenges by explicitly modeling the cellular mechanisms induced by sequence variations. Our approach takes as input genome-wide expression measurements and aims to generate a finer-grained hypothesis such as "sequence variations S induces cellular processes M, which lead to changes in the phenotype P." Furthermore, we have developed the "meta-prior algorithm" which can learn the regulatory potential of each sequence variation based on their intrinsic characteristics. This improvement helps to identify a true causal sequence variation among a number of polymorphisms in the same chromosomal region. Our approaches have led to novel insights on sequence variations, and some of the hypotheses have been validated through biological experiments. |
05/03: Systems Biology of
Microbes and Microbiomes: Reverse Ecology,
Super-Metabolism, and Metagenomic Analysis. -- Elhanan Borenstein - Genome Sciences
05/10: Sequencing a family -- Benjamin Diament
05/17: Towards a Common Informatics Framework for Biorepositories -- Paul Fearn
Abstract: Many biomedical research laboratories, departments and
organizations struggle to manage data in biospecimen repositories
that supply basic and translational research. Biorepository
information systems have been developed from a variety of
perspectives, and are often difficult to integrate or network within
and across organizations due to lack of structural and semantic
alignment with standards.
Biospecimen science is the study of the collection, processing and handling factors that affect the quality and characteristics of samples, including the their effects on the results and reproducibility of biological and biomedical investigations. To account and control for variation in samples, biorepository systems need to incorporate both workflow support and provenance information. By leveraging existing and emerging best practices, data models, data exchange formats and vocabularies, informatics can facilitate and advance the quality and reproducibility of research. This paper reviews and synthesizes requirements and standards for biorepositories and biospecimen science, and proposes a common framework. |
05/24: -- The 2010 CMB Spring Symposium: CSE 590c is preempted this week so everyone may attend the Fourth Annual CMB Spring Symposium. Seven Great Talks! All Afternoon! Coffee! Details here.
05/31: -- Holiday
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 |