Semantically Linking In Silico Cancer Models

Multiscale models are commonplace in cancer modeling, where individual models acting on different biological scales are combined within a single, cohesive modeling framework. However, model composition gives rise to challenges in understanding interfaces and interactions between them. Based on specific domain expertise, typically these computational models are developed by separate research groups using different methodologies, programming languages, and parameters. This paper introduces a graph-based model for semantically linking computational cancer models via domain graphs that can help us better understand and explore combinations of models spanning multiple biological scales. We take the data model encoded by TumorML, an XML-based markup language for storing cancer models in online repositories, and transpose its model description elements into a graph-based representation. By taking such an approach, we can link domain models, such as controlled vocabularies, taxonomic schemes, and ontologies, with cancer model descriptions to better understand and explore relationships between models. The union of these graphs creates a connected property graph that links cancer models by categorizations, by computational compatibility, and by semantic interoperability, yielding a framework in which opportunities for exploration and discovery of combinations of models become possible

Unraveling the Stratification of an Iron-Oxidizing Microbial Mat by Metatranscriptomics

International audienceA metatranscriptomic approach was used to study community gene expression in a naturally occurring iron-rich microbial mat. Total microbial community RNA was reversely transcribed and sequenced by pyrosequencing. Characterization of expressed gene sequences provided accurate and detailed information of the composition of the transcriptionally active community and revealed phylogenetic and functional stratifications within the mat. Comparison of 16S rRNA reads and delineation of OTUs showed significantly lower values of metatranscriptomic-based richness and diversity in the upper parts of the mat than in the deeper regions. Taxonomic affiliation of rRNA sequences and mRNA genome recruitments indicated that iron-oxidizing bacteria affiliated to the genus Leptothrix, dominated the community in the upper layers of the mat. Surprisingly, type I methanotrophs contributed to the majority of the sequences in the deep layers of the mat. Analysis of mRNA expression patterns showed that genes encoding the three subunits of the particulate methane monooxygenase (pmoCAB) were the most highly expressed in our dataset. These results provide strong hints that iron-oxidation and methane-oxidation occur simultaneously in microbial mats and that both groups of microorganisms are major players in the functioning of this ecosystem

Efficient and reproducible in vitro regeneration of Solanum lycopersicum and assessment genetic uniformity using flow cytometry and SPAR methods

24 p.-4 fig.-6 tab.In the present study, we develop an efficient and reproducible in vitro regeneration system for two cultivars viz., Jamila and Tomaland of Solanum lycopersicum L., an economically important vegetable crop throughout the world. Sterilization of seeds with 2.5 % (v/v) NaOCl was found to be most effective, about 97 % of seeds germinated on cotton in magenta box moistened with sterile half strength (½)Murashige and Skoog (MS) medium. Regeneration efficiency of cotyledonary leaf (CL) and cotyledonary node (CN) explants derived from 08 days old aseptic seedling were assessed on MS medium supplemented with different concentrations of auxins and cytokinin. CL explants were found more responsive in comparison to CN in both the cultivars. Types of basal media were also assessed and found to have a significant effect on shoot regeneration. Highest regeneration frequency and maximum number of shoots were standardized from CL explants on MS medium supplied with 6- benzyl adenine (BA; 5.0 µM), indole-3-butyric acid (IBA; 2.5 µM) and Kinetin (Kin; 10.0 µM). In vitro regenerated microshoots were rooted on ½MS medium containing 0.5 µM indole-3-butyric acid (IBA). Regenerated plantlets with well-developed roots and shoot system were successfully acclimated to ex vitro condition. Genetic uniformity of tissue culture raised plantlets was first time evaluated using flow cytometry and single primer amplification reaction (SPAR) methods viz., DAMD and ISSR. No significant changes in ploidy level and nuclear DNA content profile were observed between in vitro propagated plants and normal plants of both the cultivars. Similarly, the SPAR analysis also revealed monomorphic banding patterns in regenerated plantlets of S. lycopersicum verifying their genetic uniformity and clonal fidelity. This efficient regeneration system can be used as a fast and reproducible method for genetic transformation of this important vegetable crop.This project was funded by the National Plan for Science, Technology and Innovation (MAARIFAH), King Abdul Aziz City for Science and Technology, Kingdom of Saudi Arabia, Award Number 12-BIO2919-02.Peer reviewe

How do individuals with Williams syndrome learn a route in a real-world environment?

Individuals with Williams syndrome (WS) show a specific deficit in visuo-spatial abilities. This finding, however, is mainly based on performance on small-scale laboratory-based tasks. This study investigated large-scale route learning in individuals with WS and two matched control groups (moderate learning difficulty group [MLD], typically developing group [TD]). In a non-labelling and a labelling (verbal information provided along the route) condition, participants were guided along one of two unfamiliar 1 km routes with 20 junctions, and then retraced the route themselves (two trials). The WS participants performed less well than the other groups, but given verbal information and repeated experience they learnt nearly all of the turns along the route. The extent of improvement in route knowledge (correct turns) in WS was comparable to that of the control groups. Relational knowledge (correctly identifying spatial relationships between landmarks), compared to the TD group, remained poor for both the WS and MLD groups. Assessment of the relationship between performance on the large-scale route learning task to that on three small-scale tasks (maze learning, perspective taking, map use) showed no relationship for the TD controls, and only a few non-specific associations in the MLD and WS groups

Systematic identifiability testing for unambiguous mechanistic modeling – application to JAK-STAT, MAP kinase, and NF-κB signaling pathway models

<p>Abstract</p> <p>Background</p> <p>When creating mechanistic mathematical models for biological signaling processes it is tempting to include as many known biochemical interactions into one large model as possible. For the JAK-STAT, MAP kinase, and NF-<it>κ</it>B pathways a lot of biological insight is available, and as a consequence, large mathematical models have emerged. For large models the question arises whether unknown model parameters can uniquely be determined by parameter estimation from measured data. Systematic approaches to answering this question are indispensable since the uniqueness of model parameter values is essential for predictive mechanistic modeling.</p> <p>Results</p> <p>We propose an eigenvalue based method for efficiently testing identifiability of large ordinary differential models and compare this approach to three existing ones. The methods are benchmarked by applying them to models of the signaling pathways mentioned above. In all cases the eigenvalue method proposed here and the orthogonal method find the largest set of identifiable parameters, thus clearly outperforming the other approaches. The identifiability analysis shows that the pathway models are not identifiable, even under the strong assumption that all system state variables are measurable. We demonstrate how the results of the identifiability analysis can be used for model simplification.</p> <p>Conclusion</p> <p>While it has undoubtedly contributed to recent advances in systems biology, mechanistic modeling by itself does not guarantee unambiguous descriptions of biological processes. We show that some recent signal transduction pathway models have reached a level of detail that is not warranted. Rigorous identifiability tests reveal that even if highly idealized experiments could be carried out to measure all state variables of these signaling pathways, some unknown parameters could still not be estimated. The identifiability tests therefore show that the level of detail of the investigated models is too high <it>in principle</it>, not just because too little experimental information is available. We demonstrate how the proposed method can be combined with biological insight, however, to simplify these models.</p

Impact of organizational politics on employee performance in public sector organizations

The present study seeks to investigate the impact of organizational politics on employee performance in the public sector organizations. The study developed a framework on the basis of an extensive literature review which was then tested to provide an empirical insight about the proposed relationships. The data were collected from the employees of 15 public sector organizations in Pakistan. The data was statistically analyzed using regression analysis. The results revealed that organizational politics have a significant impact on employee performance. The findings of the study reinforce that the management needs to understand the perception of employees about the organizational politics prevailing in their organizations and have to adopt strategies that would minimize the perception of organizational politics and enhance employee performance. The present study has been conducted in a developing economy; therefore, the findings of the present study are partially generalized able to other developing economies as well. The future researchers can also perform the studies in other settings

Visualization of artificial skin complicatedly shaped making forms illumination

katedra: NTI; přílohy: CD ROM; rozsah: 70 s. (68 931 znaků)Diplomová práce je součástí projektu, který se zabývá inovací technologií na výrobu umělých kůží. Jde o spolupráci tří subjektů a to Technické univerzity v Liberci, společnosti Lenam s.r.o. a společnosti Magna. Cílem diplomové práce je vytvořit program, který urychlí proces rozmisťování infračervených (IR, infrared) zářičů pro ohřev forem pro umělou kůži. Pro dosažení tohoto cíle bylo potřeba implementovat nové funkce do vhodně zvoleného programu. Po provedení multikriteriální analýzy nakonec vzešel Blender jako nejvhodnější kandiát. Po implementaci těchto rozšíření již není zapotřebí několika programů a specialistů na práci v těchto programech, ale vše je spojeno v jeden program se všemi nezbytnými funkcemi. Mezi základní rozšiřující funkce patří funkce pro detekci kolizí zářičů a dále pak funkce pro zviditelnění stop zářičů. Implementovány jsou tři základní funkce pro zobrazování stop. Jsou to geometrická metoda (GEOM), metoda založená na funkcí definovaném rozložení vyzářené energie na ploše (FUNC) a metoda založená na výpočtu radiosity (RAD). Dále byly vytvořeny funkce pro měření vzdáleností jednotlivých objektů, zjišťování různých statistik apod. Pro tyto funkce bylo potřeba také vytvořit ovládací prvky a upravit grafické uživatelské rozhraní tak, aby bylo co nejvíce podobné jiným, které se používají v profesionálních počítačem podporovaných projektech (CAD, komputer aided design). Jednotlivé kapitoly jsou členěny do tří částí. První část vždy je věnována teoretickým poznatkům. Tyto poznatky jsou zužitkovány v druhé části, která se již zabývá konkrétními postupy. Na konci každé kapitoly jsou pak uvedeny výsledky a stručné zhodnocení nové funkce. Všechny popisované rozšíření jsou naprogramovány v jazyce Python. V závěru jsou uvedeny výstupy, kterých lze pomocí výsledné aplikace dosáhnout.The thesis is a part of a project which deals with innovation of technologies for production of imitation leather. The project is the cooperation of three subjects, the Technical University of Liberec, Lenam Ltd. Company and Magna Company. The aim of this thesis is to create a program which accelerates the process of arranging of IR emitters for imitation leather forms heating. To reach this aim it was necessary to implement new functions into Blender program. Thanks to these new functions there are not needed several programs and specialists for work with these programs but everything is united into one program with all indispensable functions. Among the basic extending functions there belongs the function for detection of emitters collisions and also the function for making emitters tracks visible. There are implemented three basic functions, GEOM, FUNC and RAD into the program. Then there were created functions for measuring distances of single objects, for surveying statistics etc. For these functions it was also necessary to create control components and adjust graphic user interface to be the most resembling another ones used in professional CAD systems. The first part of this thesis deals with theoretical information which is utilized in the second part that deals with particular procedures. These led to successful realization of the whole program. Programming language Python is used for Blender program and that is why all mentioned extending modules are programmed in this language. In the conclusion there are stated results which are possible to achieve thanks to the application

A simple work flow for biologically inspired model reduction - application to early JAK-STAT signaling

Abstract Background Modeling of biological pathways is a key issue in systems biology. When constructing a model, it is tempting to incorporate all known interactions of pathway species, which results in models with a large number of unknown parameters. Fortunately, unknown parameters need not necessarily be measured directly, but some parameter values can be estimated indirectly by fitting the model to experimental data. However, parameter fitting, or, more precisely, maximum likelihood parameter estimation, only provides valid results, if the complexity of the model is in balance with the amount and quality of the experimental data. If this is the case the model is said to be identifiable for the given data. If a model turns out to be unidentifiable, two steps can be taken. Either additional experiments need to be conducted, or the model has to be simplified. Results We propose a systematic procedure for model simplification, which consists of the following steps: estimate the parameters of the model, create an identifiability ranking for the estimated parameters, and simplify the model based on the identifiability analysis results. These steps need to be applied iteratively until the resulting model is identifiable, or equivalently, until parameter variances are small. We choose parameter variances as stopping criterion, since they are concise and easy to interpret. For both, the parameter estimation and the calculation of parameter variances, multi-start parameter estimations are run on a parallel cluster. In contrast to related work in systems biology, we do not suggest simplifying a model by fixing some of its parameters, but change the structure of the model. Conclusions We apply the proposed approach to a model of early signaling events in the JAK-STAT pathway. The resulting model is not only identifiable with small parameter variances, but also shows the best trade-off between goodness of fit and model complexity. </jats:sec