Background: Surveying the scientific literature is an important part of early drug discovery; and with the ever-increasing amount of biomedical publications it is imperative to focus on the most interesting articles. Here we present a project that highlights new understanding (e.g.
View Article and Find Full Text PDFColorectal cancer (CRC) is a leading cause of death worldwide. Surgical intervention is a successful treatment for stage I patients, whereas other more advanced cases may require adjuvant chemotherapy. The selection of effective adjuvant treatments remains, however, challenging.
View Article and Find Full Text PDFGene copy-number changes influence phenotypes through gene-dosage alteration and subsequent changes of protein complex stoichiometry. Human trisomies where gene copy numbers are increased uniformly over entire chromosomes provide generic cases for studying these relationships. In most trisomies, gene and protein level alterations have fatal consequences.
View Article and Find Full Text PDFTesticular germ cell cancer (TGCC) is one of the most heritable forms of cancer. Previous genome-wide association studies have focused on single nucleotide polymorphisms, largely ignoring the influence of copy number variants (CNVs). Here we present a genome-wide study of CNV on a cohort of 212 cases and 437 controls from Denmark, which was genotyped at ∼1.
View Article and Find Full Text PDFThe mitotic spindle is an essential molecular machine involved in cell division, whose composition has been studied extensively by detailed cellular biology, high-throughput proteomics, and RNA interference experiments. However, because of its dynamic organization and complex regulation it is difficult to obtain a complete description of its molecular composition. We have implemented an integrated computational approach to characterize novel human spindle components and have analysed in detail the individual candidates predicted to be spindle proteins, as well as the network of predicted relations connecting known and putative spindle proteins.
View Article and Find Full Text PDFSystems pharmacology is an emergent area that studies drug action across multiple scales of complexity, from molecular and cellular to tissue and organism levels. There is a critical need to develop network-based approaches to integrate the growing body of chemical biology knowledge with network biology. Here, we report ChemProt, a disease chemical biology database, which is based on a compilation of multiple chemical-protein annotation resources, as well as disease-associated protein-protein interactions (PPIs).
View Article and Find Full Text PDFExposure to environmental chemicals and drugs may have a negative effect on human health. A better understanding of the molecular mechanism of such compounds is needed to determine the risk. We present a high confidence human protein-protein association network built upon the integration of chemical toxicology and systems biology.
View Article and Find Full Text PDFBackground: Polymorphisms in the potassium channel, voltage-gated, KQT-like subfamily, member 1 (KCNQ1) have recently been reported to associate with type 2 diabetes. The primary aim of the present study was to investigate the putative impact of these KCNQ1 polymorphisms (rs2283228, rs2237892, rs2237895, and rs2237897) on estimates of glucose stimulated insulin release.
Methodology/principal Findings: Genotypes were examined for associations with serum insulin levels following an oral glucose tolerance test (OGTT) in a population-based sample of 6,039 middle-aged and treatment-naïve individuals.
Heritable diseases are caused by germ-line mutations that, despite tissuewide presence, often lead to tissue-specific pathology. Here, we make a systematic analysis of the link between tissue-specific gene expression and pathological manifestations in many human diseases and cancers. Diseases were systematically mapped to tissues they affect from disease-relevant literature in PubMed to create a disease-tissue covariation matrix of high-confidence associations of >1,000 diseases to 73 tissues.
View Article and Find Full Text PDFA response to Combined analysis reveals a core set of cycling genes by Y Lu, S Mahony, PV Benos, R Rosenfeld, I Simon, LL Breeden and Z Bar-Joseph. Genome Biol 2007, 8:R146.
View Article and Find Full Text PDFThe past decade has seen the publication of a large number of cell-cycle microarray studies and many more are in the pipeline. However, data from these experiments are not easy to access, combine and evaluate. We have developed a centralized database with an easy-to-use interface, Cyclebase.
View Article and Find Full Text PDFDecades of research has together with the availability of whole genomes made it clear that many of the core components involved in the cell cycle are conserved across eukaryotes, both functionally and structurally. These proteins are organized in complexes and modules that are activated or deactivated at specific stages during the cell cycle through a wide variety of mechanisms including transcriptional regulation, phosphorylation, subcellular translocation and targeted degradation. In a series of integrative analyses of different genome-scale data sets, we have studied how these different layers of regulation together control the activity of cell cycle complexes and how this regulation has evolved.
View Article and Find Full Text PDFDNA microarray studies have shown that hundreds of genes are transcribed periodically during the mitotic cell cycle of humans, budding yeast, fission yeast and the plant Arabidopsis thaliana. Here we show that despite the fact the protein complexes involved in this process are largely the same among all eukaryotes, their regulation has evolved considerably. Our comparative analysis of several large-scale data sets reveals that although the regulated subunits of each protein complex are expressed just before its time of action, the identity of the periodically expressed proteins differs significantly between organisms.
View Article and Find Full Text PDFWe present an approach combining bioinformatics prediction with experimental microarray validation to identify new cell cycle-regulated genes in Saccharomyces cerevisiae. We identify in the order of 100 new cell cycle-regulated genes and show by independent data that these genes in general tend to be more weakly expressed than the genes identified hitherto. Among the genes not previously suggested to be periodically expressed we find genes linked to DNA repair, cell size monitoring and transcriptional control, as well as a number of genes of unknown function.
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