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Identifying DNA Sequence Motifs of Pdx-1 and NeuroD1 Transcription Factors
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Diabetes is a disease reported to be the 8th leading cause of death across the world. Nearly 38 million people worldwide have Type I diabetes caused by a dysfunction of beta cells that impairs insulin production. A better understanding of mechanisms related to gene expression in beta cells might help in the development of novel strategies for the effective treatment of diabetes. Two known transcription factors, Pdx-1 and NeuroD1, are shown to regulate gene expression in beta cells. Recently gene targets that are regulated by both Pdx-1 and NeuroD1 have been identified experimentally [7]. However, the motifs for this set of genes have not been found yet. Here we undertake the task of finding statistically overrepresented motifs in genes regulated by Pdx-1 and NeuroD1. The challenge of this project is to identify statistically significant pairs of motifs: one motif of each pair is for Pdx-1 and the other for NeuroD1. Commonly known motif-finding methods are usually restricted to finding a set of potential candidates, each of which is a single motif.
Title: Identifying DNA Sequence Motifs of Pdx-1 and NeuroD1 Transcription Factors
Description:
Diabetes is a disease reported to be the 8th leading cause of death across the world.
Nearly 38 million people worldwide have Type I diabetes caused by a dysfunction of beta cells that impairs insulin production.
A better understanding of mechanisms related to gene expression in beta cells might help in the development of novel strategies for the effective treatment of diabetes.
Two known transcription factors, Pdx-1 and NeuroD1, are shown to regulate gene expression in beta cells.
Recently gene targets that are regulated by both Pdx-1 and NeuroD1 have been identified experimentally [7].
However, the motifs for this set of genes have not been found yet.
Here we undertake the task of finding statistically overrepresented motifs in genes regulated by Pdx-1 and NeuroD1.
The challenge of this project is to identify statistically significant pairs of motifs: one motif of each pair is for Pdx-1 and the other for NeuroD1.
Commonly known motif-finding methods are usually restricted to finding a set of potential candidates, each of which is a single motif.
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