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Generating inferences from a gene regulatory network is important to understand the fundamental cellular processes, involving gene functions, and their relations. The availability of time-series gene expression data makes it possible to investigate the gene activities of the whole genomes. Under this framework, gene interaction is explained through a(More)
Human papillomavirus type 16 (HPV16) can cause cervical cancer. Expression of the viral E1 E4 protein is lost during malignant progression, but in premalignant lesions, E1 E4 is abundant in cells supporting viral DNA amplification. Expression of 16E1 E4 in cell culture causes G2 cell cycle arrest. Here we show that unlike many other G2 arrest mechanisms,(More)
The E1--E4 protein of human papillomavirus type 16 (HPV16) causes cytokeratin reorganization in the middle and upper epithelial layers and is thought to contribute to multiple facets of the virus life cycle. Although little is known as to how HPV16 E1--E4 (16E1--E4) functions are controlled following the first expression of this protein, the finding that(More)
The human papillomavirus type 16 E1--E4 protein is expressed abundantly in cells supporting viral DNA amplification, but its expression is lost during malignant progression. In cell culture, 16E1--E4 causes G2 cell cycle arrest by associating with and preventing the nuclear entry of Cdk1/cyclin B1 complexes. Here, we show that 16E1--E4 is also able to(More)
Kinase-insert domain-containing receptor (KDR) is one of the important mediators of Vascular endothelial growth factor (VEGF) function in endothelial cells. Inhibition of KDR can be therapeutically advantageous for treatment of a number of diseases. The present study focuses on exploring novel KDR inhibitors by means of pharmaco-informatics methodologies.(More)
Generating inferences from a gene regulatory network is important to understand the fundamental cellular processes, involving gene functions, and their relations. The availability of time-series gene expression data makes it possible to investigate the gene activities of the whole genomes. Under this framework, gene interaction is explained through a set of(More)
Generating inferences from a gene regulatory network is important to understand the fundamental cellular processes, involving gene functions, and their relations. The availability of time-series gene expression data makes it possible to investigate the gene activities of the whole genomes. Under this framework, gene interaction is explained through a(More)
The cDNA for bubaline beta-lactoglobulin (beta lg) has been cloned through RT-PCR approach and sequenced. Sequence data showed a single open reading frame coding for a protein of 180 amino acids with a signal sequence of 18 amino acid residues. Comparison with other ruminant beta lg sequences revealed a high homology indicating the protein to be conserved(More)