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Bioinformatics Tool Development And Sequence Analysis Of Rosaceae Family Expressed Sequence Tags, Margaret Staton May 2007

Bioinformatics Tool Development And Sequence Analysis Of Rosaceae Family Expressed Sequence Tags, Margaret Staton

All Dissertations

BACKGROUND: An international community of researchers has generated a significant number of Expressed Sequence Tags (ESTs) for the Rosaceae, an economically important plant family that includes most temperate fruits such as apple, cherry, peach, and strawberry as well as other commercially valuable members. ESTs are fragments of expressed genes that can be used for gene discovery, developing markers for mapping and cultivar improvement via marker assisted selection. Efficient dissemination and integration of this data is best facilitated through a centralized and curated database with associated sequence analysis tools.

DESCRIPTION: The Genome Database for Rosaceae (GDR) was initiated to provide a …


Finding Molecular Complexes Through Multiple Layer Clustering Of Protein Interaction Networks, Bill Andreopoulos, Aijun An, Xiangji Huang, Xiaogang Wang Jan 2007

Finding Molecular Complexes Through Multiple Layer Clustering Of Protein Interaction Networks, Bill Andreopoulos, Aijun An, Xiangji Huang, Xiaogang Wang

Faculty Publications, Computer Science

Clustering protein-protein interaction networks (PINs) helps to identify complexes that guide the cell machinery. Clustering algorithms often create a flat clustering, without considering the layered structure of PINs. We propose the MULIC clustering algorithm that produces layered clusters. We applied MULIC to five PINs. Clusters correlate with known MIPS protein complexes. For example, a cluster of 79 proteins overlaps with a known complex of 88 proteins. Proteins in top cluster layers tend to be more representative of complexes than proteins in bottom layers. Lab work on finding unknown complexes or determining drug effects can be guided by top layer proteins.


Identification And Characterization Of The Rat Dvl2 Gene Using Bioinformatic Tools, Lokman Varişli, Osman Çen Jan 2007

Identification And Characterization Of The Rat Dvl2 Gene Using Bioinformatic Tools, Lokman Varişli, Osman Çen

Turkish Journal of Biology

We identified and characterized the rat DVL2 gene using bioinformatics. In addition to the structure and chromosomal localization of the rat DVL2 gene, the transcribed and translated protein product of the gene was analyzed in silico. Results showed that the rat DVL2 gene consists of 15 exons and is located on the rat genomic contig WGA1854.3 on chromosome 10. Database searches using the rat DVL2 amino acid sequence as a query showed a number of homologous protein sequences in different species, including M. musculus, P. troglodytes, C. familiaris, H. sapiens, B. taurus, D. rerio, X. laevis, and T. nigroviridis. DAX, …


Finding Molecular Complexes Through Multiple Layer Clustering Of Protein Interaction Networks, Bill Andreopoulos, Aijun An, Xiangji Huang, Xiaogang Wang Dec 2006

Finding Molecular Complexes Through Multiple Layer Clustering Of Protein Interaction Networks, Bill Andreopoulos, Aijun An, Xiangji Huang, Xiaogang Wang

William B. Andreopoulos

Clustering protein-protein interaction networks (PINs) helps to identify complexes that guide the cell machinery. Clustering algorithms often create a flat clustering, without considering the layered structure of PINs. We propose the MULIC clustering algorithm that produces layered clusters. We applied MULIC to five PINs. Clusters correlate with known MIPS protein complexes. For example, a cluster of 79 proteins overlaps with a known complex of 88 proteins. Proteins in top cluster layers tend to be more representative of complexes than proteins in bottom layers. Lab work on finding unknown complexes or determining drug effects can be guided by top layer proteins.