Annotations for Rule-Based Models

The chapter reviews the syntax to store machine-readable annotations and describes the mapping between rule-based modelling entities (e.g., agents and rules) and these annotations. In particular, we review an annotation framework and the associated guidelines for annotating rule-based models of molecular interactions, encoded in the commonly used Kappa and BioNetGen languages, and present prototypes that can be used to extract and query the annotations. An ontology is used to annotate models and facilitate their description

Ranked retrieval of Computational Biology models

<p>Abstract</p> <p>Background</p> <p>The study of biological systems demands computational support. If targeting a biological problem, the reuse of existing computational models can save time and effort. Deciding for potentially suitable models, however, becomes more challenging with the increasing number of computational models available, and even more when considering the models' growing complexity. Firstly, among a set of potential model candidates it is difficult to decide for the model that best suits ones needs. Secondly, it is hard to grasp the nature of an unknown model listed in a search result set, and to judge how well it fits for the particular problem one has in mind.</p> <p>Results</p> <p>Here we present an improved search approach for computational models of biological processes. It is based on existing retrieval and ranking methods from Information Retrieval. The approach incorporates annotations suggested by MIRIAM, and additional meta-information. It is now part of the search engine of BioModels Database, a standard repository for computational models.</p> <p>Conclusions</p> <p>The introduced concept and implementation are, to our knowledge, the first application of Information Retrieval techniques on model search in Computational Systems Biology. Using the example of BioModels Database, it was shown that the approach is feasible and extends the current possibilities to search for relevant models. The advantages of our system over existing solutions are that we incorporate a rich set of meta-information, and that we provide the user with a relevance ranking of the models found for a query. Better search capabilities in model databases are expected to have a positive effect on the reuse of existing models.</p

Snazer: the simulations and networks analyzer

<p>Abstract</p> <p>Background</p> <p>Networks are widely recognized as key determinants of structure and function in systems that span the biological, physical, and social sciences. They are static pictures of the interactions among the components of complex systems. Often, much effort is required to identify networks as part of particular patterns as well as to visualize and interpret them.</p> <p>From a pure dynamical perspective, simulation represents a relevant <it>way</it>-<it>out</it>. Many simulator tools capitalized on the "noisy" behavior of some systems and used formal models to represent cellular activities as temporal trajectories. Statistical methods have been applied to a fairly large number of replicated trajectories in order to infer knowledge.</p> <p>A tool which both graphically manipulates reactive models and deals with sets of simulation time-course data by aggregation, interpretation and statistical analysis is missing and could add value to simulators.</p> <p>Results</p> <p>We designed and implemented <it>Snazer</it>, the simulations and networks analyzer. Its goal is to aid the processes of visualizing and manipulating reactive models, as well as to share and interpret time-course data produced by stochastic simulators or by any other means.</p> <p>Conclusions</p> <p><it>Snazer </it>is a solid prototype that integrates biological network and simulation time-course data analysis techniques.</p

Estrogen Promotes Mandibular Condylar Fibrocartilage Chondrogenesis and Inhibits Degeneration via Estrogen Receptor Alpha in Female Mice

Temporomandibular joint degenerative disease (TMJ-DD) is a chronic form of TMJ disorder that specifically afflicts people over the age of 40 and targets women at a higher rate than men. Prevalence of TMJ-DD in this population suggests that estrogen loss plays a role in the disease pathogenesis. Thus, the goal of the present study was to determine the role of estrogen on chondrogenesis and homeostasis via estrogen receptor alpha (ERα) during growth and maturity of the joint. Young and mature WT and ERαKO female mice were subjected to ovariectomy procedures and then given placebo or estradiol treatment. The effect of estrogen via ERα on fibrocartilage morphology, matrix production, and protease activity was assessed. In the young mice, estrogen via ERα promoted mandibular condylar fibrocartilage chondrogenesis partly by inhibiting the canonical Wnt signaling pathway through upregulation of sclerostin (Sost). In the mature mice, protease activity was partly inhibited with estrogen treatment via the upregulation and activity of protease inhibitor 15 (Pi15) and alpha-2- macroglobulin (A2m). The results from this work provide a mechanistic understanding of estradiol on TMJ growth and homeostasis and can be utilized for development of therapeutic targets to promote regeneration and inhibit degeneration of the mandibular condylar fibrocartilage.National Institute of Dental & Craniofacial Research of the National Institutes of Health under Award Numbers R56DE020097 (SW) and F32DE026366 (JR

Apoptosis induction in Jurkat cells and sCD95 levels in women's sera are related with the risk of developing cervical cancer

<p>Abstract</p> <p>Background</p> <p>Currently, there is clear evidence that apoptosis plays an important role in the development and progression of tumors. One of the best characterized apoptosis triggering systems is the CD95/Fas/APO-1 pathway; previous reports have demonstrated high levels of soluble CD95 (sCD95) in serum of patients with some types of cancer. Cervical cancer is the second most common cancer among women worldwide. As a first step in an attempt to design a minimally invasive test to predict the risk of developing cervical cancer in patients with precancerous lesions, we used a simple assay based on the capacity of human serum to induce apoptosis in Jurkat cells. We evaluated the relationship between sCD95 levels and the ability to induce apoptosis in Jurkat cells in cervical cancer patients and controls.</p> <p>Methods</p> <p>Jurkat cells were exposed to serum from 63 women (20 healthy volunteers, 21 with cervical intraepithelial neoplasia grade I [CIN 1] and 22 with cervical-uterine carcinoma). The apoptotic rate was measured by flow cytometry using Annexin-V-Fluos and Propidium Iodide as markers. Serum levels of sCD95 and soluble CD95 ligand (sCD95L) were measured by ELISA kits.</p> <p>Results</p> <p>We found that serum from almost all healthy women induced apoptosis in Jurkat cells, while only fifty percent of the sera from women with CIN 1 induced cell death in Jurkat cells. Interestingly, only one serum sample from a patient with cervical-uterine cancer was able to induce apoptosis, the rest of the sera protected Jurkat cells from this killing. We were able to demonstrate that elimination of Jurkat cells was mediated by the CD95/Fas/Apo-1 apoptotic pathway. Furthermore, the serum levels of sCD95 measured by ELISA were significantly higher in women with cervical cancer.</p> <p>Conclusion</p> <p>Our results demonstrate that there is a strong correlation between low levels of sCD95 in serum of normal women and higher apoptosis induction in Jurkat cells. We suggest that an analysis of the apoptotic rate induced by serum in Jurkat cells and the levels of sCD95 in serum could be helpful during the prognosis and treatment of women detected with precancerous lesions or cervical cancer.</p

Genome-wide association study identifies 48 common genetic variants associated with handedness

Handedness has been extensively studied because of its relationship with language and the over-representation of left-handers in some neurodevelopmental disorders. Using data from the UK Biobank, 23andMe and the International Handedness Consortium, we conducted a genome-wide association meta-analysis of handedness (N = 1,766,671). We found 41 loci associated (P < 5 × 10-8) with left-handedness and 7 associated with ambidexterity. Tissue-enrichment analysis implicated the CNS in the aetiology of handedness. Pathways including regulation of microtubules and brain morphology were also highlighted. We found suggestive positive genetic correlations between left-handedness and neuropsychiatric traits, including schizophrenia and bipolar disorder. Furthermore, the genetic correlation between left-handedness and ambidexterity is low (rG = 0.26), which implies that these traits are largely influenced by different genetic mechanisms. Our findings suggest that handedness is highly polygenic and that the genetic variants that predispose to left-handedness may underlie part of the association with some psychiatric disorders