Tag Archives: seattle biomed

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: Educational Outreach Real-time Strategy Immune Response Game

Con­tact Name: Samuel Danziger

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

Depart­ment: Seattle Biomed

Descrip­tion:

Immunology is complicated and stuff has strange names, and this makes it very hard for students of all ages to learn immunology.  However, many video games and fantasy worlds are similarly complex and strange, but many school children can tell you about them in painstaking detail.  Fortunately, the immune system is a perfect fit for a real time strategy (RTS) game with macrophages killing invaders and dendritic cells gathering resources to build yet more powerful invader-killing cells. We’ve spec’ed out level progression and basic game mechanics, and are hoping to get an alpha version of the game together so we can shop around for financial backing (currently unfunded, enthusiast beware.).

Require­ments:

Basic programming skills.
Proficiency or willingness to learn Unity or similar game development platform.

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