Bioelectrical Impedance Vector Pattern and Biomarkers of Physical Functioning of Prostate Cancer Survivors in Rehabilitation.

Background: Knowledge of clinically established factors of physical function such as body composition, bioelectrical phase angle (PhA) and handgrip strength (HGS) with mortality predictive and health-related relevance is limited in prostate cancer survivors (PCS). Therefore, the aim of this study was to characterise and compare body composition data of PCS with extensive reference data as well as to analyse PhA and HGS and the prevalence of critical prognostic values at an early stage of cancer survivorship.

Methods: One hundred and forty-eight PCS were examined at the start (T1) and end (T2) of a 3-week hospitalised urooncological rehabilitation, which began median 28 days after acute cancer therapy.

Ontologizer 2.0--a multifunctional tool for GO term enrichment analysis and data exploration.

Unlabelled: The Ontologizer is a Java application that can be used to perform statistical analysis for overrepresentation of Gene Ontology (GO) terms in sets of genes or proteins derived from an experiment. The Ontologizer implements the standard approach to statistical analysis based on the one-sided Fisher's exact test, the novel parent-child method, as well as topology-based algorithms. A number of multiple-testing correction procedures are provided.

Improved detection of overrepresentation of Gene-Ontology annotations with parent child analysis.

Motivation: High-throughput experiments such as microarray hybridizations often yield long lists of genes found to share a certain characteristic such as differential expression. Exploring Gene Ontology (GO) annotations for such lists of genes has become a widespread practice to get first insights into the potential biological meaning of the experiment. The standard statistical approach to measuring overrepresentation of GO terms cannot cope with the dependencies resulting from the structure of GO because they analyze each term in isolation.

A new statistical model to select target sequences bound by transcription factors.

Transcription factors (TFs) play a key role in gene regulation by binding to target sequences. In silico prediction of potential binding to a sequence is a main task in computational biology. Although many methods have been proposed to tackle this problem, the statistical significance of the prediction is still not solved.

Simultaneous alignment and annotation of cis-regulatory regions.

Motivation: Current methods that annotate conserved transcription factor binding sites in an alignment of two regulatory regions perform the alignment and annotation step separately and combine the results in the end. If the site descriptions are weak or the sequence similarity is low, the local gap structure of the alignment poses a problem in detecting the conserved sites. It is therefore desirable to have an approach that is able to simultaneously consider the alignment as well as possibly matching site locations.

Rap1A-deficient T and B cells show impaired integrin-mediated cell adhesion.

Studies in tissue culture cells have demonstrated a role for the Ras-like GTPase Rap1 in the regulation of integrin-mediated cell-matrix and cadherin-mediated cell-cell contacts. To analyze the function of Rap1 in vivo, we have disrupted the Rap1A gene by homologous recombination. Mice homozygous for the deletion allele are viable and fertile.

T-Reg Comparator: an analysis tool for the comparison of position weight matrices.

T-Reg Comparator is a novel software tool designed to support research into transcriptional regulation. Sequence motifs representing transcription factor binding sites are usually encoded as position weight matrices. The user inputs a set of such weight matrices or binding site sequences and our program matches them against the T-Reg database, which is presently built on data from the Transfac [E.

Comparative promoter region analysis powered by CORG.

Background: Promoters are key players in gene regulation. They receive signals from various sources (e.g.