Muc4/Muc4 Functions And Regulation In Cancer., Goldi Kozloski
Dec 2009
Muc4/Muc4 Functions And Regulation In Cancer., Goldi Kozloski
Goldi A Kozloski
The membrane mucin MUC4 (human) is abundantly expressed in many epithelia, where it is proposed to play a protective role, and is overexpressed in some epithelial tumors. Studies on the rat homologue, Muc4, indicate that it acts through anti-adhesive or signaling mechanisms. In particular, Muc4/MUC4 can serve as a ligand/modulator of the receptor tyrosine kinase ErbB2, regulating its phosphorylation and the phosphorylation of its partner ErbB3, with or without the involvement of the ErbB3 ligand neuregulin. Muc4/MUC4 can also modulate cell apoptosis via multiple mechanisms, both ErbB2 dependent and independent. Muc4/MUC4 expression is regulated by multiple mechanisms, ranging from transcriptional …
Conformational Changes In Receptor Tyrosine Kinase Signaling: An Erbb Garden Of Delights., Goldi Kozloski
Sep 2009
Conformational Changes In Receptor Tyrosine Kinase Signaling: An Erbb Garden Of Delights., Goldi Kozloski
Goldi A Kozloski
The ErbB family of receptor tyrosine kinases plays important roles in cell proliferation, differentiation, and apoptosis. Recent structural studies of these receptors have demonstrated dramatic conformational effects that are critical to their ligand binding and activation, and have shown that these receptors provide levels of control beyond the classic dimerization/activation mechanism. These results indicate that this class of receptors has evolved subtle regulatory mechanisms via genetic and protein structural changes to influence their effects on cell behaviors.
Integrative Analysis Of Cancer Genomic Data, Shuangge Ma
Sep 2009
Integrative Analysis Of Cancer Genomic Data, Shuangge Ma
Shuangge Ma
In the past decade, we have witnessed a period of unparallel development in the field of cancer genomics. To address the same or similar biomedical questions, multiple cancer genomic studies have been independently designed and conducted. Cancer gene signatures identified from analysis of individual datasets often have low reproducibility. A cost-effective way of improving reproducibility is to conduct integrative analysis of datasets from multiple studies with comparable designs. To properly integrate multiple studies and conduct integrative analysis, we need to access various public data warehouses, retrieve experiment protocols and raw data, evaluate individual studies and select those with comparable designs, …
Identification Of Cancer-Associated Gene Pathways From Analysis Of Expression Data, Shuangge Ma
Aug 2009
Identification Of Cancer-Associated Gene Pathways From Analysis Of Expression Data, Shuangge Ma
Shuangge Ma
No abstract provided.
Identification Of Synechococcus Sp. Iu 625 Phycocyanin Gene And Bioinformatic Analyses Of Cyanobacterial Phycocyanin., Tin-Chun Chu, Aline Oliveira, Arti Rana, Lee Lee
Jun 2009
Identification Of Synechococcus Sp. Iu 625 Phycocyanin Gene And Bioinformatic Analyses Of Cyanobacterial Phycocyanin., Tin-Chun Chu, Aline Oliveira, Arti Rana, Lee Lee
Tin-Chun Chu, Ph.D.
No abstract provided.
Triangle Network Motifs Predict Complexes By Complementing High-Error Interactomes With Structural Information, Bill Andreopoulos, Christof Winter, Dirk Labudde, Michael Schroeder
Jun 2009
Triangle Network Motifs Predict Complexes By Complementing High-Error Interactomes With Structural Information, Bill Andreopoulos, Christof Winter, Dirk Labudde, Michael Schroeder
William B. Andreopoulos
Background
A lot of high-throughput studies produce protein-protein interaction networks (PPINs) with many errors and missing information. Even for genome-wide approaches, there is often a low overlap between PPINs produced by different studies. Second-level neighbors separated by two protein-protein interactions (PPIs) were previously used for predicting protein function and finding complexes in high-error PPINs. We retrieve second level neighbors in PPINs, and complement these with structural domain-domain interactions (SDDIs) representing binding evidence on proteins, forming PPI-SDDI-PPI triangles.
Results
We find low overlap between PPINs, SDDIs and known complexes, all well below 10%. We evaluate the overlap of PPI-SDDI-PPI triangles with …
Lecture 5, Shuangge Ma
Jun 2009
Lecture 5, Shuangge Ma
Shuangge Ma
No abstract provided.
Final Project, Shuangge Ma
Jun 2009
Final Project, Shuangge Ma
Shuangge Ma
No abstract provided.
Lecture 4, Shuangge Ma
Jun 2009
Lecture 4, Shuangge Ma
Shuangge Ma
No abstract provided.
Lecture 4, Shuangge Ma
Jun 2009
Lecture 4, Shuangge Ma
Shuangge Ma
No abstract provided.
Computer Intensive Methods Lecture 13, Shuangge Ma
Jun 2009
Computer Intensive Methods Lecture 13, Shuangge Ma
Shuangge Ma
No abstract provided.
Final Project (Description), Shuangge Ma
Jun 2009
Final Project (Description), Shuangge Ma
Shuangge Ma
No abstract provided.
Final Project (Data), Shuangge Ma
Jun 2009
Final Project (Data), Shuangge Ma
Shuangge Ma
No abstract provided.
Lecture 3, Shuangge Ma
Jun 2009
Lecture 3, Shuangge Ma
Shuangge Ma
No abstract provided.
Lecture 2, Shuangge Ma
Jun 2009
Lecture 2, Shuangge Ma
Shuangge Ma
No abstract provided.
Reference: Multiple Imputation, Shuangge Ma
Jun 2009
Reference: Multiple Imputation, Shuangge Ma
Shuangge Ma
No abstract provided.
Reference: Weighted Bootstrap, Shuangge Ma
Jun 2009
Reference: Weighted Bootstrap, Shuangge Ma
Shuangge Ma
No abstract provided.
Computer Intensive Methods Lecture 9, Shuangge Ma
Jun 2009
Computer Intensive Methods Lecture 9, Shuangge Ma
Shuangge Ma
No abstract provided.
Computer Intensive Methods Lecture 8, Shuangge Ma
Jun 2009
Computer Intensive Methods Lecture 8, Shuangge Ma
Shuangge Ma
No abstract provided.
Reference: Counter Examples [Bootstrap], Shuangge Ma
Jun 2009
Reference: Counter Examples [Bootstrap], Shuangge Ma
Shuangge Ma
No abstract provided.
Computer Intensive Methods Lecture 7 (Lab 2), Shuangge Ma
Jun 2009
Computer Intensive Methods Lecture 7 (Lab 2), Shuangge Ma
Shuangge Ma
No abstract provided.
Computer Intensive Methods Lecture 6, Shuangge Ma
Jun 2009
Computer Intensive Methods Lecture 6, Shuangge Ma
Shuangge Ma
No abstract provided.
Reference: Block Jackknife, Shuangge Ma
Jun 2009
Reference: Block Jackknife, Shuangge Ma
Shuangge Ma
No abstract provided.
Computer Intensive Methods Lecture 5, Shuangge Ma
Jun 2009
Computer Intensive Methods Lecture 5, Shuangge Ma
Shuangge Ma
No abstract provided.
Reading: Simulate Multivariate Distribution, Shuangge Ma
Jun 2009
Reading: Simulate Multivariate Distribution, Shuangge Ma
Shuangge Ma
No abstract provided.
Computer Intensive Methods Lecture 4, Shuangge Ma
Jun 2009
Computer Intensive Methods Lecture 4, Shuangge Ma
Shuangge Ma
No abstract provided.
Computer Intensive Methods Lecture 3 (Lab 1), Shuangge Ma
Jun 2009
Computer Intensive Methods Lecture 3 (Lab 1), Shuangge Ma
Shuangge Ma
No abstract provided.
Computer Intensive Methods Lecture 2, Shuangge Ma
Jun 2009
Computer Intensive Methods Lecture 2, Shuangge Ma
Shuangge Ma
No abstract provided.
A Tale Of Two Streets: Incorporating Grouping Structure In High Dimensional Data Mining, Shuangge Ma
Jun 2009
A Tale Of Two Streets: Incorporating Grouping Structure In High Dimensional Data Mining, Shuangge Ma
Shuangge Ma
No abstract provided.
Catena-Poly[[(Pyridine-Κn)Copper(Ii)]-Μ3-Pyridine-2,6-Dicarboxylato-Κ3o2:O2′,N,O6:O6′], Manoj Trivedi, Daya Shankar Pandey, Nigam P. Rath
Mar 2009
Catena-Poly[[(Pyridine-Κn)Copper(Ii)]-Μ3-Pyridine-2,6-Dicarboxylato-Κ3o2:O2′,N,O6:O6′], Manoj Trivedi, Daya Shankar Pandey, Nigam P. Rath
Nigam Rath
In the title compound, [Cu(C7H3NO4)(C5H5N)]n, the CuII atom is in a slightly distorted octahedral coordination environment. Each CuII atom is bound to two N atoms and one O atom of the pyridinedicarboxylate (PDA) ligand in a tridentate manner, one N atom of the pyridine molecule and two bridging carboxylate O atoms of adjacent PDA ligands, leading to a linear one-dimensional chain running along the c axis. These chains are further assembled via weak C-H...O and [pi]-[pi] interactions into a three-dimensional supramolecular network structure. The centroid-centroid distance between the [pi]-[pi] interacting pyridine rings is 3.9104 (13) Å. The two N atoms …
