StemNet: An Evolving Service for Knowledge Networking in the Life Sciences

Up until now, crucial life science information resources, whether bibliographic or factual databases, are isolated from each other. Moreover, semantic metadata intended to structure their contents is supplied in a manual form only. In the StemNet project we aim at developing a framework for semantic interoperability for these resources. This will facilitate the extraction of relevant information from textual sources and the generation of semantic metadata in a fully automatic manner. In this way, (from a computational perspective) unstructured life science documents are linked to structured biological fact databases, in particular to the identifiers of genes, proteins, etc. Thus, life scientists will be able to seamlessly access information from a homogeneous platform, despite the fact that the original information was unlinked and scattered over the whole variety of heterogeneous life science information resources and, therefore, almost inaccessible for integrated systematic search by academic, clinical, or industrial users

Modeling the Development of Goal-Specificity in Mirror Neurons

Neurophysiological studies have shown that parietal mirror neurons encode not only actions but also the goal of these actions. Although some mirror neurons will fire whenever a certain action is perceived (goal-independently), most will only fire if the motion is perceived as part of an action with a specific goal. This result is important for the action-understanding hypothesis as it provides a potential neurological basis for such a cognitive ability. It is also relevant for the design of artificial cognitive systems, in particular robotic systems that rely on computational models of the mirror system in their interaction with other agents. Yet, to date, no computational model has explicitly addressed the mechanisms that give rise to both goal-specific and goal-independent parietal mirror neurons. In the present paper, we present a computational model based on a self-organizing map, which receives artificial inputs representing information about both the observed or executed actions and the context in which they were executed. We show that the map develops a biologically plausible organization in which goal-specific mirror neurons emerge. We further show that the fundamental cause for both the appearance and the number of goal-specific neurons can be found in geometric relationships between the different inputs to the map. The results are important to the action-understanding hypothesis as they provide a mechanism for the emergence of goal-specific parietal mirror neurons and lead to a number of predictions: (1) Learning of new goals may mostly reassign existing goal-specific neurons rather than recruit new ones; (2) input differences between executed and observed actions can explain observed corresponding differences in the number of goal-specific neurons; and (3) the percentage of goal-specific neurons may differ between motion primitives

Imputation Rules to Improve the Education Variable in the IAB Employment Subsample

The education variable in the IAB employment subsample has two shortcomings: missing values and inconsistencies with the reporting rule. We propose several deductive imputation procedures to improve the variable. They mainly use the multiple education information available in the data because the employees' education is reported at least once a year. We compare the improved data from the different procedures and the original data in typical applications in labor economics: educational composition of employment, wage inequality, and wage regression. We find, that correcting the education variable: (i) shows the educational attainment of the male labor force to be higher than measured with the original data, (ii) gives different values for some measures of wage inequality, and (iii) does not change the estimates in wage regressions much

A novel mutation Thr162Arg of the melanocortin 4 receptor gene in a Spanish children and adolescent population

Objective  The melanocortin 4 receptor gene (MC4R) is involved in body weight regulation. While many studies associated MC4R mutations with childhood obesity, information on MC4R mutations in Spanish children and adolescents is lacking. Our objective was to screen a population of children and adolescents from the north of Spain (Navarra) for MC4R mutations and to study the phenotypes of carriers and their families. In addition, functional assays were performed for a novel MC4R mutation. Methods  The study was composed of 451 Spanish children and adolescents (49% boys), aged 5–18 year. According to the International Obesity Task Force (IOTF) criteria, the groups included 160 obese, 132 overweight and 159 normal-weight control subjects. Results  One novel (Thr162Arg) and three known nonsynonymous mutations in the MC4R gene (Ser30Phe, Thr150Ile, Ala244Glu) were detected heterozygously. The MC4R mutations were found in three male (one obese and two overweight) and two female subjects (one obese and one overweight). The novel mutation did not appear to lead to an impaired receptor function. An unequivocal relationship of MC4R mutations with obesity in pedigrees together with an impaired function of the encoded receptor could not be established for any of the mutations. Conclusions  The presence of heterozygous MC4R mutations in obese and overweight subjects indicates that these mutations may be a susceptibility factor for obesity development, but lifestyle factors, such as exercise or sedentary activities, may modify their effect

The Bone Dysplasia Ontology: integrating genotype and phenotype information in the skeletal dysplasia domain

<p>Abstract</p> <p>Background</p> <p>Skeletal dysplasias are a rare and heterogeneous group of genetic disorders affecting skeletal development. Patients with skeletal dysplasias suffer from many complex medical issues including degenerative joint disease and neurological complications. Because the data and expertise associated with this field is both sparse and disparate, significant benefits will potentially accrue from the availability of an ontology that provides a shared conceptualisation of the domain knowledge and enables data integration, cross-referencing and advanced reasoning across the relevant but distributed data sources.</p> <p>Results</p> <p>We introduce the design considerations and implementation details of the Bone Dysplasia Ontology. We also describe the different components of the ontology, including a comprehensive and formal representation of the skeletal dysplasia domain as well as the related genotypes and phenotypes. We then briefly describe SKELETOME, a community-driven knowledge curation platform that is underpinned by the Bone Dysplasia Ontology. SKELETOME enables domain experts to use, refine and extend and apply the ontology without any prior ontology engineering experience--to advance the body of knowledge in the skeletal dysplasia field.</p> <p>Conclusions</p> <p>The Bone Dysplasia Ontology represents the most comprehensive structured knowledge source for the skeletal dysplasias domain. It provides the means for integrating and annotating clinical and research data, not only at the generic domain knowledge level, but also at the level of individual patient case studies. It enables links between individual cases and publicly available genotype and phenotype resources based on a community-driven curation process that ensures a shared conceptualisation of the domain knowledge and its continuous incremental evolution.</p

Autism genetic database (AGD): a comprehensive database including autism susceptibility gene-CNVs integrated with known noncoding RNAs and fragile sites

<p>Abstract</p> <p>Background</p> <p>Autism is a highly heritable complex neurodevelopmental disorder, therefore identifying its genetic basis has been challenging. To date, numerous susceptibility genes and chromosomal abnormalities have been reported in association with autism, but most discoveries either fail to be replicated or account for a small effect. Thus, in most cases the underlying causative genetic mechanisms are not fully understood. In the present work, the Autism Genetic Database (AGD) was developed as a literature-driven, web-based, and easy to access database designed with the aim of creating a comprehensive repository for all the currently reported genes and genomic copy number variations (CNVs) associated with autism in order to further facilitate the assessment of these autism susceptibility genetic factors.</p> <p>Description</p> <p>AGD is a relational database that organizes data resulting from exhaustive literature searches for reported susceptibility genes and CNVs associated with autism. Furthermore, genomic information about human fragile sites and noncoding RNAs was also downloaded and parsed from miRBase, snoRNA-LBME-db, piRNABank, and the MIT/ICBP siRNA database. A web client genome browser enables viewing of the features while a web client query tool provides access to more specific information for the features. When applicable, links to external databases including GenBank, PubMed, miRBase, snoRNA-LBME-db, piRNABank, and the MIT siRNA database are provided.</p> <p>Conclusion</p> <p>AGD comprises a comprehensive list of susceptibility genes and copy number variations reported to-date in association with autism, as well as all known human noncoding RNA genes and fragile sites. Such a unique and inclusive autism genetic database will facilitate the evaluation of autism susceptibility factors in relation to known human noncoding RNAs and fragile sites, impacting on human diseases. As a result, this new autism database offers a valuable tool for the research community to evaluate genetic findings for this complex multifactorial disorder in an integrated format. AGD provides a genome browser and a web based query client for conveniently selecting features of interest. Access to AGD is freely available at <url>http://wren.bcf.ku.edu/</url>.</p

Analysis of sequence variations in the suppressor of cytokine signaling (SOCS)-3 gene in extremely obese children and adolescents

BACKGROUND: The suppressor of cytokine signaling (SOCS)-3 is a negative feedback regulator of cytokine signaling and also influences leptin signaling. We investigated association of variations in the coding sequence and promoter region of SOCS3 with extreme obesity in German children and adolescents. METHODS: An initial screen for sequence variations in 181 extremely obese children and adolescents and 188 healthy underweight adults revealed two previously reported single nucleotide polymorphisms (SNPs) in the SOCS3 5' region: -1044 C>A (numbering refers to bases upstream of ATG in exon 2) within a predicted STAT3 binding element and -920 C>A (rs12953258, for numbering, see above). RESULTS: We did not detect significant differences in allele or genotype frequencies for any of these SNPs between the analysed study groups (all nominal p > 0.2). In addition, we performed a pedigree transmission disequilibrium test (PDT) for the SNP -1044 C>A in families comprising 703 obese children and adolescents, 281 of their obese siblings and both biological parents. The PDT revealed no transmission disequilibrium (nominal p > 0.05). CONCLUSION: In conclusion, our data do not suggest evidence for a major role of the respective SNPs in SOCS3 in the pathogenesis of extreme obesity in our study groups