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Articles 1 - 4 of 4
Full-Text Articles in Bioinformatics
Muc4 Modulation Of Ligand-Independent Erbb2 Signaling, Goldi Attias Kozloski
Muc4 Modulation Of Ligand-Independent Erbb2 Signaling, Goldi Attias Kozloski
Goldi A Kozloski
The membrane mucin Muc4 is a heterodimer, bi-functional glycoprotein complex that is normally expressed in epithelial tissue. Functional studies on the extracellular mucin subunit of Muc4 have shown that it acts to promote anti-adhesion properties by sterically interfering with cell-cell and cell-matrix interactions and that the extent of this effect is directly associated with the number of tandem repeats on this subunit. Functional studies on the transmembrane subunit of Muc4 have shown that this subunit participates in intracellular signaling through interaction with the receptor tyrosine kinase ErbB2. This role of Muc4 was shown to be mediated by stabilizing the heregulin …
Micrornas Are Independent Predictors Of Outcome In Diffuse Large B-Cell Lymphoma Patients Treated With R-Chop, Goldi Kozloski
Micrornas Are Independent Predictors Of Outcome In Diffuse Large B-Cell Lymphoma Patients Treated With R-Chop, Goldi Kozloski
Goldi A Kozloski
Evolution And Quantitative Comparison Of Genome-Wide Protein Domain Distributions, Arli A. Parikesit, Peter F. Stadler, Sonja J. Prohaska
Evolution And Quantitative Comparison Of Genome-Wide Protein Domain Distributions, Arli A. Parikesit, Peter F. Stadler, Sonja J. Prohaska
Arli A Parikesit
The metabolic and regulatory capabilities of an organism are implicit in its protein content. This is often hard to estimate, however, due to ascertainment biases inherent in the available genome annotations. Its complement of recognizable functional protein domains and their combinations convey essentially the same information and at the same time are much more readily accessible, although protein domain models trained for one phylogenetic group frequently fail on distantly related sequences. Pooling related domain models based on their GO-annotation in combination with de novo gene prediction methods provides estimates that seem to be less affected by phylogenetic biases. We show …
Evolution Of Domain Co-Occurrences: Some Striking Results, Arli A. Parikesit, Peter F. Stadler, Sonja J. Prohaska
Evolution Of Domain Co-Occurrences: Some Striking Results, Arli A. Parikesit, Peter F. Stadler, Sonja J. Prohaska
Arli A Parikesit
No abstract provided.