TIde: a software for the systematic scanning of drug targets in kinetic network models

<p>Abstract</p> <p>Background</p> <p>During the stages of the development of a potent drug candidate compounds can fail for several reasons. One of them, the efficacy of a candidate, can be estimated <it>in silico </it>if an appropriate ordinary differential equation model of the affected pathway is available. With such a model at hand it is also possible to detect reactions having a large effect on a certain variable such as a substance concentration.</p> <p>Results</p> <p>We show an algorithm that systematically tests the influence of activators and inhibitors of different type and strength acting at different positions in the network. The effect on a quantity to be selected (e.g. a steady state flux or concentration) is calculated. Moreover, combinations of two inhibitors or one inhibitor and one activator targeting different network positions are analysed. Furthermore, we present TIde (Target Identification), an open source, platform independent tool to investigate ordinary differential equation models in the common systems biology markup language format. It automatically assigns the respectively altered kinetics to the inhibited or activated reactions, performs the necessary calculations, and provides a graphical output of the analysis results. For illustration, TIde is used to detect optimal inhibitor positions in simple branched networks, a signalling pathway, and a well studied model of glycolysis in <it>Trypanosoma brucei</it>.</p> <p>Conclusion</p> <p>Using TIde, we show in the branched models under which conditions inhibitions in a certain pathway can affect a molecule concentrations in a different. In the signalling pathway we illuminate which inhibitions have an effect on the signalling characteristics of the last active kinase. Finally, we compare our set of best targets in the glycolysis model with a similar analysis showing the applicability of our tool.</p

Classified AGV Material Flow and Layout Data Set for Multidisciplinary Investigation

Automated Guided Vehicles (AGV) are increasingly used in industry to automate material flow tasks. To efficiently operate systems of AGVs, researchers have proposed many different planning and control methods, e.g., for scheduling, dispatching, and routing. The performance of these methods depends on the characteristics of the system, such as transport distances and station operation frequencies. Even though these characteristics strongly influence the algorithms, no classified collection of layout data was found based on a scientific literature review. In this paper, a data set of 72 material flow and layout compositions from the scientific literature (42) and German industry (30) is presented. Each composition in the data set consists of a transport matrix and a distance matrix. To classify the compositions, a holistic taxonomy was established based on distinguishing criteria for material flow and layout compositions known from the scientific literature. The compositions were classified according to the taxonomy. An analysis of the station operation frequency and transport distance distribution data reveals typical characteristics of the compositions as well as variations between the classified compositions. The aim of this data set is to allow benchmarking of planning and control methods, thus increasing the transparency and traceability of scientific work. Furthermore, the analysis of the layouts and their taxonomy allows to compare the methods of different disciplines. By providing standardized, machine readable formats, automatic testing and optimization will be possible

Characterization of White Matter Hyperintensities in Large-Scale MRI-Studies

Background: White matter hyperintensities of presumed vascular origin (WMH) are a common finding in elderly people and a growing social malady in the aging western societies. As a manifestation of cerebral small vessel disease, WMH are considered to be a vascular contributor to various sequelae such as cognitive decline, dementia, depression, stroke as well as gait and balance problems. While pathophysiology and therapeutical options remain unclear, large-scale studies have improved the understanding of WMH, particularly by quantitative assessment of WMH. In this review, we aimed to provide an overview of the characteristics, research subjects and segmentation techniques of these studies.Methods: We performed a systematic review according to the PRISMA statement. One thousand one hundred and ninety-six potentially relevant articles were identified via PubMed search. Six further articles classified as relevant were added manually. After applying a catalog of exclusion criteria, remaining articles were read full-text and the following information was extracted into a standardized form: year of publication, sample size, mean age of subjects in the study, the cohort included, and segmentation details like the definition of WMH, the segmentation method, reference to methods papers as well as validation measurements.Results: Our search resulted in the inclusion and full-text review of 137 articles. One hundred and thirty-four of them belonged to 37 prospective cohort studies. Median sample size was 1,030 with no increase over the covered years. Eighty studies investigated in the association of WMH and risk factors. Most of them focussed on arterial hypertension, diabetes mellitus type II and Apo E genotype and inflammatory markers. Sixty-three studies analyzed the association of WMH and secondary conditions like cognitive decline, mood disorder and brain atrophy. Studies applied various methods based on manual (3), semi-automated (57), and automated segmentation techniques (75). Only 18% of the articles referred to an explicit definition of WMH.Discussion: The review yielded a large number of studies engaged in WMH research. A remarkable variety of segmentation techniques was applied, and only a minority referred to a clear definition of WMH. Most addressed topics were risk factors and secondary clinical conditions. In conclusion, WMH research is a vivid field with a need for further standardization regarding definitions and used methods

Propagating semantic information in biochemical network models

<p>Abstract</p> <p>Background</p> <p>To enable automatic searches, alignments, and model combination, the elements of systems biology models need to be compared and matched across models. Elements can be identified by machine-readable biological annotations, but assigning such annotations and matching non-annotated elements is tedious work and calls for automation.</p> <p>Results</p> <p>A new method called "semantic propagation" allows the comparison of model elements based not only on their own annotations, but also on annotations of surrounding elements in the network. One may either propagate feature vectors, describing the annotations of individual elements, or quantitative similarities between elements from different models. Based on semantic propagation, we align partially annotated models and find annotations for non-annotated model elements.</p> <p>Conclusions</p> <p>Semantic propagation and model alignment are included in the open-source library semanticSBML, available on sourceforge. Online services for model alignment and for annotation prediction can be used at <url>http://www.semanticsbml.org</url>.</p

Colossal magnetoresistance in EuZn2_2P2_2 and its electronic and magnetic structure

We investigate single crystals of the trigonal antiferromagnet EuZn$_2$P$_2$ ($P\overline{3}m1$) by means of electrical transport, magnetization measurements, X-ray magnetic scattering, optical reflectivity, angle-resolved photoemission spectroscopy (ARPES) and ab-initio band structure calculations (DFT+U). We find that the electrical resistivity of EuZn$_2$P$_2$ increases strongly upon cooling and can be suppressed in magnetic fields by several orders of magnitude (CMR effect). Resonant magnetic scattering reveals a magnetic ordering vector of $q = (0\, 0\, \frac{1}{2})$, corresponding to an $A$-type antiferromagnetic (AFM) order, below $T_{\rm N} = 23.7\,\rm K$. We find that the moments are canted out of the $a-a$ plane by an angle of about $40^{\circ}\pm 10^{\circ}$ degrees and tilted away from the [100] - direction by $30^{\circ}\pm 5^{\circ}$. We observe nearly isotropic magnetization behavior for low fields and low temperatures which is consistent with the magnetic scattering results. The magnetization measurements show a deviation from the Curie-Weiss behavior below $\approx 150\,\rm K$, the temperature below which also the field dependence of the material's resistivity starts to increase. An analysis of the infrared reflectivity spectrum at $T=295\,\rm K$ allows us to resolve the main phonon bands and intra-/interband transitions, and estimate indirect and direct band gaps of $E_i^{\mathrm{opt}}=0.09\,\rm{eV}$ and $E_d^{\mathrm{opt}}=0.33\,\rm{eV}$, respectively, which are in good agreement with the theoretically predicted ones. The experimental band structure obtained by ARPES is nearly $T$-independent above and below $T_{\rm N}$. The comparison of the theoretical and experimental data shows a weak intermixing of the Eu 4$f$ states close to the $\Gamma$ point with the bands formed by the phosphorous 3$p$ orbitals leading to an induction of a small magnetic moment at the P sites