Bioinformatics

The analysis of gene regulatory networks (GRNs) is a central goal of bioinformatics highly accelerated by the advent of new experimental techniques, such as RNA interference. A battery of reverse engineering methods has been developed in recent years to reconstruct the underlying GRNs from these and other experimental data. However, the performance of the individual methods is poorly understood and validation of algorithmic performances is still missing to a large extent. To enable such systematic validation, we have developed the web application GeNGe (GEne Network GEnerator), a controlled framework for the automatic generation of GRNs. The theoretical model for a GRN is a non-linear differential equation system. Networks can be user-defined or constructed in a modular way with the option to introduce global and local network perturbations. Resulting data can be used, e.g. as benchmark data for evaluating GRN reconstruction methods or for predicting effects of perturbations as theoretical counterparts of biological experiment

ConsensusPathDB: toward a more complete picture of cell biology

ConsensusPathDB is a meta-database that integrates different types of functional interactions from heterogeneous interaction data resources. Physical protein interactions, metabolic and signaling reactions and gene regulatory interactions are integrated in a seamless functional association network that simultaneously describes multiple functional aspects of genes, proteins, complexes, metabolites, etc. With 155,432 human, 194,480 yeast and 13,648 mouse complex functional interactions (originating from 18 databases on human and eight databases on yeast and mouse interactions each), ConsensusPathDB currently constitutes the most comprehensive publicly available interaction repository for these species. The Web interface at http://cpdb.molgen.mpg.de offers different ways of utilizing these integrated interaction data, in particular with tools for visualization, analysis and interpretation of high-throughput expression data in the light of functional interactions and biological pathways

Single-particle spectral function for the classical one-component plasma

The spectral function for an electron one-component plasma is calculated self-consistently using the GW0 approximation for the single-particle self-energy. In this way, correlation effects which go beyond the mean-field description of the plasma are contained, i.e. the collisional damping of single-particle states, the dynamical screening of the interaction and the appearance of collective plasma modes. Secondly, a novel non-perturbative analytic solution for the on-shell GW0 self-energy as a function of momentum is presented. It reproduces the numerical data for the spectral function with a relative error of less than 10% in the regime where the Debye screening parameter is smaller than the inverse Bohr radius, kappa<1/a_B. In the limit of low density, the non-perturbative self-energy behaves as n^(1/4), whereas a perturbation expansion leads to the unphysical result of a density independent self-energy [W. Fennel and H. P. Wilfer, Ann. Phys. Lpz._32_, 265 (1974)]. The derived expression will greatly facilitate the calculation of observables in correlated plasmas (transport properties, equation of state) that need the spectral function as an input quantity. This is demonstrated for the shift of the chemical potential, which is computed from the analytical formulae and compared to the GW0-result. At a plasma temperature of 100 eV and densities below 10^21 cm^-3, both approaches deviate less than 10% from each other.Comment: 14 pages, 9 figures accepted for publication in Phys. Rev. E v2: added section V (application of presented formalism to chemical potential of the OCP

Primary differentiation in the human blastocyst : comparative molecular portraits of inner cell mass and trophectoderm cells

The primary differentiation event during mammalian development occurs at the blastocyst stage and leads to the delineation of the inner cell mass (ICM) and the trophectoderm (TE). We provide the first global mRNA expression data from immunosurgically dissected ICM cells, TE cells, and intact human blastocysts. Using a cDNA microarray composed of 15,529 cDNAs from known and novel genes, we identify marker transcripts specific to the ICM (e.g., OCT4/POU5F1, NANOG, HMGB1, and DPPA5) and TE (e.g., CDX2, ATP1B3, SFN, and IPL), in addition to novel ICM- and TE-specific expressed sequence tags. The expression patterns suggest that the emergence of pluripotent ICM and TE cell lineages from the morula is controlled by metabolic and signaling pathways, which include inter alia, WNT, mitogen-activated protein kinase, transforming growth factor-beta, NOTCH, integrin-mediated cell adhesion, phosphatidylinositol 3-kinase, and apoptosis. These data enhance our understanding of the first step in human cellular differentiation and, hence, the derivation of both embryonic stem cells and trophoblastic stem cells from these lineages

Antisymmetrization of a Mean Field Calculation of the T-Matrix

The usual definition of the prior(post) interaction $V(V^\prime )$ between projectile and target (resp. ejectile and residual target) being contradictory with full antisymmetrization between nucleons, an explicit antisymmetrization projector ${\cal A}$ must be included in the definition of the transition operator, $T\equiv V^\prime{\cal A}+V^\prime{\cal A}GV.$ We derive the suitably antisymmetrized mean field equations leading to a non perturbative estimate of $T$. The theory is illustrated by a calculation of forward $\alpha$-$\alpha$ scattering, making use of self consistent symmetries.Comment: 30 pages, no figures, plain TeX, SPHT/93/14

High-Throughput miRNA and mRNA Sequencing of Paired Colorectal Normal, Tumor and Metastasis Tissues and Bioinformatic Modeling of miRNA-1 Therapeutic Applications

MiRNAs are discussed as diagnostic and therapeutic molecules. However, effective miRNA drug treatments with miRNAs are, so far, hampered by the complexity of the miRNA networks. To identify potential miRNA drugs in colorectal cancer, we profiled miRNA and mRNA expression in matching normal, tumor and metastasis tissues of eight patients by Illumina sequencing. We validated six miRNAs in a large tissue screen containing 16 additional tumor entities and identified miRNA-1, miRNA-129, miRNA-497 and miRNA-215 as constantly de-regulated within the majority of cancers. Of these, we investigated miRNA-1 as representative in a systems-biology simulation of cellular cancer models implemented in PyBioS and assessed the effects of depletion as well as overexpression in terms of miRNA-1 as a potential treatment option. In this system, miRNA-1 treatment reverted the disease phenotype with different effectiveness among the patients. Scoring the gene expression changes obtained through mRNA-Seq from the same patients we show that the combination of deep sequencing and systems biological modeling can help to identify patient-specific responses to miRNA treatments. We present this data as guideline for future pre-clinical assessments of new and personalized therapeutic options

Experimental validation of computerised models of clustering of platelet glycoprotein receptors that signal via tandem SH2 domain proteins

The clustering of platelet glycoprotein receptors with cytosolic YxxL and YxxM motifs, including GPVI, CLEC-2 and PEAR1, triggers activation via phosphorylation of the conserved tyrosine residues and recruitment of the tandem SH2 (Src homology 2) domain effector proteins, Syk and PI 3-kinase. We have modelled the clustering of these receptors with monovalent, divalent and tetravalent soluble ligands and with transmembrane ligands based on the law of mass action using ordinary differential equations and agent-based modelling. The models were experimentally evaluated in platelets and transfected cell lines using monovalent and multivalent ligands, including novel nanobody-based divalent and tetravalent ligands, by fluorescence correlation spectroscopy. Ligand valency, receptor number, receptor dimerisation, receptor phosphorylation and a cytosolic tandem SH2 domain protein act in synergy to drive receptor clustering. Threshold concentrations of a CLEC-2-blocking antibody and Syk inhibitor act in synergy to block platelet aggregation. This offers a strategy for countering the effect of avidity of multivalent ligands and in limiting off-target effects

Self-consistent Spectral Function for Non-Degenerate Coulomb Systems and Analytic Scaling Behaviour

Novel results for the self-consistent single-particle spectral function and self-energy are presented for non-degenerate one-component Coulomb systems at various densities and temperatures. The GW^0-method for the dynamical self-energy is used to include many-particle correlations beyond the quasi-particle approximation. The self-energy is analysed over a broad range of densities and temperatures (n=10^17/cm^3-10^27/cm^3, T=10^2 eV/k_B-10^4 eV/k_B). The spectral function shows a systematic behaviour, which is determined by collective plasma modes at small wavenumbers and converges towards a quasi-particle resonance at higher wavenumbers. In the low density limit, the numerical results comply with an analytic scaling law that is presented for the first time. It predicts a power-law behaviour of the imaginary part of the self-energy, Im Sigma ~ -n^(1/4). This resolves a long time problem of the quasi-particle approximation which yields a finite self-energy at vanishing density.Comment: 28 pages, 9 figure