Multifunctional genes

In this paper a sensor fusion for pose estimation using optical and inertial data is presented. The proposed algorithm is based on extended Kalman filtering and fuses data from an optical tracking system and an inertial measurement unit. These two redundant sensor systems complement each other well, with the tracking providing absolute position accuracy and the inertial measurements giving low latency information of derivatives. Models for both sensors are given respecting the different sampling times and latencies. Another key issue is to use information about every landmark, i.e. marker, visible for the tracking system, by coupling the two sensor systems tightly together. The algorithms are evaluated in simulation and tested with an experimental hardware platform. The combined sensor system provides robust pose estimation in case of short time marker occlusion and effectively compensates for latencies the pose measurements

Improved quality control processing of peptide-centric LC-MS proteomics data

Motivation: In the analysis of differential peptide peak intensities (i.e. abundance measures), LC-MS analyses with poor quality peptide abundance data can bias downstream statistical analyses and hence the biological interpretation for an otherwise high-quality dataset. Although considerable effort has been placed on assuring the quality of the peptide identification with respect to spectral processing, to date quality assessment of the subsequent peptide abundance data matrix has been limited to a subjective visual inspection of run-by-run correlation or individual peptide components. Identifying statistical outliers is a critical step in the processing of proteomics data as many of the downstream statistical analyses [e.g. analysis of variance (ANOVA)] rely upon accurate estimates of sample variance, and their results are influenced by extreme values

An integrated approach for the systematic identification and characterization of heart-enriched genes with unknown functions

<p>Abstract</p> <p>Background</p> <p>High throughput techniques have generated a huge set of biological data, which are deposited in various databases. Efficient exploitation of these databases is often hampered by a lack of appropriate tools, which allow easy and reliable identification of genes that miss functional characterization but are correlated with specific biological conditions (e.g. organotypic expression).</p> <p>Results</p> <p>We have developed a simple algorithm (DGSA = Database-dependent Gene Selection and Analysis) to identify genes with unknown functions involved in organ development concentrating on the heart. Using our approach, we identified a large number of yet uncharacterized genes, which are expressed during heart development. An initial functional characterization of genes by loss-of-function analysis employing morpholino injections into zebrafish embryos disclosed severe developmental defects indicating a decisive function of selected genes for developmental processes.</p> <p>Conclusion</p> <p>We conclude that DGSA is a versatile tool for database mining allowing efficient selection of uncharacterized genes for functional analysis.</p

Factors influencing rod photoreceptor differentiation in the mouse retina: a focus on insulin-like growth factor 1

Previous studies have identified several genes important in rod genesis, however, there is little information on how these genes are regulated during development. The purpose of this dissertation is to identify and investigate factors influencing rod photoreceptor differentiation. Using high throughput gene and protein expression data we have identified several factors as good candidates for involvement in rod photoreceptor development. We are specifically investigating insulin-like growth factor 1 (IGF-1) and how it affects the molecular network controlling rod photoreceptor differentiation.;IGF-1 is a growth factor present in the developing retina and has previously been shown to influence proliferation, differentiation, and survival of retinal neurons. We characterized IGF-1 receptor expression in developing and mature rod photoreceptors using immunohistochemical methods. IGF-1 receptor immunoreactivity was detected in the outer neuroblastic layer in the embryonic retina and in developing and mature rods in postnatal and adult mice. Using a serum free retinal explant culture system we have investigated the effects of long term exposure to IGF-1 on E17 and P0 mouse retinas. Application of exogenous IGF-1 significantly increased rhodopsin expression at both time points. Thus we have demonstrated a specific role for IGF-1 in promoting rod photoreceptor differentiation. In addition we have shown that IGF-1 acts through a MAP kinase independent pathway to mediate the increase in rods. Our studies are the first to demonstrate a role for IGF-1 in rod photoreceptor differentiation in the murine retina