Tag Archives: statistics

Research Opportunity: Bioengineering with the Yeast Gene Regulatory Network 2.0

Con­tact Name: Samuel Danziger

Con­tact Email: sam.danziger[at]seattlebiomed.org

Depart­ment: Seattle Biomed

Descrip­tion:

We have a developed a predictive environment and gene regulatory influence network (EGRIN) for S. Cerevisiae.  This network uses publicly available and in-house gene expression data from microarrays to predict genetic regulation and cellular responses.  We intend to expand it to a stochastically robust EGRIN 2.0 that we will use to engineer yeast to produce economically relevant compounds in peroxisomes.

10-week Project #1:  Write a framework for generating multiple EGRINs so that the EGRIN 2.0 can be generated with additional processor time.  This project would involving using the gene biclustering program cMonkey in [R] or python and interacting with a Sun Grid Engine cluster. There would be plenty of opportunity to improve the cMonkey algorithm.

Require­ments:

Familiarity with the [R] statistical programming language or Python.
Familiarity with Unix shell scripting and cluster computing using the Sun Grid Engine (SGE) or similar system.

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Research Opportunity: Malaria Resistance in Mixed Infection

Con­tact Name: Sam Danziger

Con­tact Email: sam.danziger[at]seattlebiomed.org

Depart­ment: Seattle Biomed

Descrip­tion:

We have completed a pilot study using protein arrays with children in Papua New Guinea to study mixed infection of P. Falciparum and P. Vivax malaria causing parasites.  These experiments have allowed us to identify combinations of antigens that correlate with resistance to malaria fever.  We hope the follow-up studies will ultimately lead to a malaria vaccine, especially one that works in areas with multiple parasites.

10-week Project #1:  The data involves 224 children in Papua New Guinea who were each tested for serum response to 4441 antigen polypeptides.  Each of these children was either suffering from malaria fever, or had developed a malaria resistance.  For this project, the student would expand a deep learning module written in [R] to detect relevant antigen combinations encoded in the hidden layer(s) and improve the classifier.  There would be plenty of opportunity to compare results with known (dynamic) malaria surface adhesion molecules.

10-week Project #2: Seven other centers around the globe have used the same array for similar studies.  This project would involve retrieving and curating the data from published studies (as well as through contacts with the company that prints/analyzes the arrays) and formulating research questions to explore with the combined data set.  There would be plenty of opportunity to apply / develop / expand machine learning and analysis techniques developed in the original study.

Require­ments:

Familiarity with [R] statistical programming language or similar programming language.

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Research Opportunity: Exon Array for Disease Classification

Con­tact Name: Samuel Danziger

Con­tact Email: sam.danziger[at]seattlebiomed.org

Depart­ment: Seattle Biomed

Descrip­tion:

We are exploring exon arrays on serum response cells to detect alternative splicing events that act as disease biomarkers and possibly give clues to the mechanism of disease progression.  We are currently applying this technology to investigate ALS (i.e. Lou-Gehrig Disease) in mice and Alzheimer’s Disease in humans.  We expect these techniques to transition from exon arrays to RNA-seq as the technology progresses. The idea is to train a discriminating classifier to predict ALS on the basis of features derived from the exon array.  We have currently used the FIRMA algorithm to predict alternative splicing events and an ensemble of classifiers to make predictions. Techniques developed in this project are also applied to HIV related data sets.

10-week Project #1:   For this project, the student would expand a deep learning module written in [R] (or other language) with an eye to using the hidden layer(s) to improve the classifier and possibly identify gene network pathways. There would be plenty of opportunity to apply / develop / expand machine learning and analysis techniques for both disease classification and biomarker discovery.

 

Require­ments:

Experience with [R] statistical programming language.

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Research Opportunity: Brain Imaging Biomarkers of Neurodegeneration and Injury

Con­tact Name: Donna Cross

Con­tact Email: dcross[at]uw.edu

Depart­ment: Radiology

Descrip­tion:

My lab uses brain imaging modalities such as MRI and PET to investigate neurodegenerative processes and the physiological consequence of brain injury in animal models as well as human subjects. We currently have several projects in these areas that might be suitable for undergraduate research. Potential student benefits include technical skills and knowledge of imaging sciences.

Require­ments:

Student applicants should be comfortable with analytical computing environments. Background and/or interests in basic statistics, computer programming, animal behavioral research and tissue processing would be beneficial. 10-15 hours/week commitment

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Research Opportunity: Statistical analysis of large genetic data sets

Con­tact Name: Sharon Browning

Con­tact Email: sguy[at]uw.edu

Depart­ment: Biostatistics

Descrip­tion:

Our group, led by Dr. Sharon Browning in Biostatistics and Dr. Brian Browning in Medical Genetics, develops statistically-powerful, computationally-efficient methods for analyzing large genetic data sets such as those from whole genome sequencing of large cohorts.

This project involves using software developed by our group to analyze a unique, cutting-edge genetic data set from a large dairy cow population.  The goal will be to assess the quality of the results under different settings and approaches to make recommendations for best practices.  Ultimately, this work will help dairy breeders to improve the herds.

Require­ments:

A strong background in computing and/or statistics is required.  Usually we will consider only Juniors and Seniors with a GPA of at least 3.7.  Please include a copy of your unofficial transcript with your e-mail inquiry.

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