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Student Poster Day on Computational Biology hosted by
Assistant Professor Will Fairbrother
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The First Annual Computational Biology Poster Session was held in Room 105 of the Center for Genomics and
Proteomics on Friday, May 5th, 2006, from 3:00-5:00pm. Posters ranged from image processing, to simulation of protein
nucleic acid recognition events, to the development of special alignment tools for non-coding regulatory elements.
It was a great opportunity to meet students and faculty interested in Computational Biology here at Brown.
First prize was awarded to Srividya Kalyanaraman for her poster entitled "Viral Genomes: An Insight Into
the Past and the Future".
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Author: Srividya Kalyanaraman
Viral Genomes: An Insight into the Past and the Future
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Abstract:
Viruses have been seen as both friend and foe during their time of existence. In doing alignments, it becomes
evident that viruses have genomes that render them sufficient candidates for being the precursors of eukaryotes.
When comparing the Rous Sarcoma Virus (RSV) to products it affects, the genome of RSV itself contains regions
homologous to most of its products. Also data run between Mimivirus and several different ancient human endogenous
retroviruses (HERVs) show great homology between them all.
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Authors: Lee Flowers and James Potter
The Identification of Functional Polymorphisms within Non-Coding
Sequence Elements
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Abstract:
Exon splicing enhancers (ESEs) affect the splicing of genes and their resulting
phenotypes. To better catalogue human ESEs, we propose a strategy of searching the
human genome for conserved areas to compare results with ESE motif searching algorithms.
The combination of conservation and motif searches should reduce the currently unacceptable
false positive rate in predicted splicing enhancers. Further analysis and biochemical
tests will later confirm or disconfirm ESEs from the predicted regions.
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Author: John Cumbers, Graduate Student, EEB
Modeling insulin sensitivity
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Abstract:
Models are used to make predictions about biological systems. When making a model
some simplifications must be made to make the problem tractable. A negative feedback
mechanism has recently been shown to regulate insulin receptor levels and a model
of the insulin-signaling pathway is presented here using differential equations.
The output displays the key characteristics of this negative feedback loop under
two different inputs. When fed a constant input of nutrients a typical diet in the
USA), the model mimics reduced receptor number and reduced sensitivity, which would
in turn lead to higher glucose levels and over production of insulin by the pancreas
(a pre-diabetic state). If pancreatic beta cell burn out is the pathology of diabetes,
then when no more insulin can be produced the patient develops type II diabetes.
However, when fed a cyclic input of nutrients (a more natural diet evolved from
a hunter gatherer) the model exhibits normal cyclic output of insulin and no diabetes.
Author: Lian Rae Garton
A Study of the Genes Involved in Regulatory Pathways of the Heart
Abstract:
The huge amount of available genomic data makes it important to establish various
levels for looking at the data, from the cell, to organs, to the organism. This
project focused on the specific genes active in the heart, along with an understanding
of the regulatory pathways involving those genes. I considered a number of individual
genes involved in regulatory pathways of the heart and performed comparisons across
organisms in an effort to gain a broader understanding of the relationships between
genes at the nucleotide and protein levels.
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