226 research outputs found
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Exploring and linking biomedical resources through multidimensional semantic spaces
Background
The semantic integration of biomedical resources is still a challenging issue which is required for effective information processing and data analysis. The availability of comprehensive knowledge resources such as biomedical ontologies and integrated thesauri greatly facilitates this integration effort by means of semantic annotation, which allows disparate data formats and contents to be expressed under a common semantic space. In this paper, we propose a multidimensional representation for such a semantic space, where dimensions regard the different perspectives in biomedical research (e.g., population, disease, anatomy and protein/genes).
Results
This paper presents a novel method for building multidimensional semantic spaces from semantically annotated biomedical data collections. This method consists of two main processes: knowledge and data normalization. The former one arranges the concepts provided by a reference knowledge resource (e.g., biomedical ontologies and thesauri) into a set of hierarchical dimensions for analysis purposes. The latter one reduces the annotation set associated to each collection item into a set of points of the multidimensional space. Additionally, we have developed a visual tool, called 3D-Browser, which implements OLAP-like operators over the generated multidimensional space. The method and the tool have been tested and evaluated in the context of the Health-e-Child (HeC) project. Automatic semantic annotation was applied to tag three collections of abstracts taken from PubMed, one for each target disease of the project, the Uniprot database, and the HeC patient record database. We adopted the UMLS Meta-thesaurus 2010AA as the reference knowledge resource.
Conclusions
Current knowledge resources and semantic-aware technology make possible the integration of biomedical resources. Such an integration is performed through semantic annotation of the intended biomedical data resources. This paper shows how these annotations can be exploited for integration, exploration, and analysis tasks. Results over a real scenario demonstrate the viability and usefulness of the approach, as well as the quality of the generated multidimensional semantic spaces
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Building conceptual spaces for exploring and linking biomedical resources
The establishment of links between data (e.g., patient records) and Web resources (e.g., literature) and the proper visualization of such discovered knowledge is still a challenge in most Life Science domains (e.g., biomedicine). In this paper we present our contribution to the community in the form of an infrastructure to annotate information resources, to discover relationships among them, and to represent and visualize the new discovered knowledge. Furthermore, we have also implemented a Web-based prototype tool which integrates the proposed infrastructure
Automatic symbolic modelling of co-evolutionarily learned robot skills
Proceeding of: 6th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2001 Granada, Spain, June 13–15, 2001Evolutionary based learning systems have proven to be very powerful techniques for solving a wide range of tasks, from prediction to optimization. However, in some cases the learned concepts are unreadable for humans. This prevents a deep semantic analysis of what has been really learned by those systems. We present in this paper an alternative to obtain symbolic models from subsymbolic learning. In the first stage, a subsymbolic learning system is applied to a given task. Then, a symbolic classifier is used for automatically generating the symbolic counterpart of the subsymbolic model. We have tested this approach to obtain a symbolic model of a neural network. The neural network defines a simple controller af an autonomous robot. a competitive coevolutive method has been applied in order to learn the right weights of the neural network. The results show that the obtained symbolic model is very accurate in the task of modelling the subsymbolic system, adding to this its readability characteristic
The Effect of Single Nucleotide Polymorphisms from Genome Wide Association Studies in Multiple Sclerosis on Gene Expression
BACKGROUND: Multiple sclerosis (MS) is a complex neurological disorder. Its aetiology involves both environmental and genetic factors. Recent genome-wide association studies have identified a number of single nucleotide polymorphisms (SNPs) associated with susceptibility to (MS). We investigated whether these genetic variations were associated with alteration in gene expression. METHODS/PRINCIPAL FINDINGS: We used a database of mRNA expression and genetic variation derived from immortalised peripheral lymphocytes to investigate polymorphisms associated with MS for correlation with gene expression. Several SNPs were found to be associated with changes in expression: in particular two with HLA-DQA1, HLA-DQA2, HLA-DQB1, HLA-DRB1, HLA-DRB4 and HLA-DRB5, one with ZFP57, one with CD58, two with IL7 and FAM164A, and one with FAM119B, TSFM and KUB3. We found minimal cross-over with a recent whole genome expression study in MS patients. DISCUSSION: We have shown that many susceptibility loci in MS are associated with changes in gene expression using an unbiased expression database. Several of these findings suggest novel gene candidates underlying the effects of MS-associated genetic variation
Reuse of terminological resources for efficient ontological engineering in Life Sciences
This paper is intended to explore how to use terminological resources for ontology engineering. Nowadays there are several biomedical ontologies describing overlapping domains, but there is not a clear correspondence between the concepts that are supposed to be equivalent or just similar. These resources are quite precious but their integration and further development are expensive. Terminologies may support the ontological development in several stages of the lifecycle of the ontology; e.g. ontology integration. In this paper we investigate the use of terminological resources during the ontology lifecycle. We claim that the proper creation and use of a shared thesaurus is a cornerstone for the successful application of the Semantic Web technology within life sciences. Moreover, we have applied our approach to a real scenario, the Health-e-Child (HeC) project, and we have evaluated the impact of filtering and re-organizing several resources. As a result, we have created a reference thesaurus for this project, named HeCTh
Central nervous system relapse in high-risk stage 4 neuroblastoma : the HR-NBL1/SIOPEN trial experience
Vitamin D receptor ChIP-seq in primary CD4+ cells: relationship to serum 25-hydroxyvitamin D levels and autoimmune disease
PMCID: PMC3710212This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
FTLD-TDP assemblies seed neoaggregates with subtype-specific features via a prion-like cascade
Morphologically distinct TDP-43 aggregates occur in clinically different FTLD-TDP subtypes, yet the mechanism of their emergence and contribution to clinical heterogeneity are poorly understood. Several lines of evidence suggest that pathological TDP-43 follows a prion-like cascade, but the molecular determinants of this process remain unknown. We use advanced microscopy techniques to compare the seeding properties of pathological FTLD-TDP-A and FTLD-TDP-C aggregates. Upon inoculation of patient-derived aggregates in cells, FTLD-TDP-A seeds amplify in a template-dependent fashion, triggering neoaggregation more efficiently than those extracted from FTLD-TDP-C patients, correlating with the respective disease progression rates. Neoaggregates are sequentially phosphorylated with N-to-C directionality and with subtype-specific timelines. The resulting FTLD-TDP-A neoaggregates are large and contain densely packed fibrils, reminiscent of the pure compacted fibrils present within cytoplasmic inclusions in postmortem brains. In contrast, FTLD-TDP-C dystrophic neurites show less dense fibrils mixed with cellular components, and their respective neoaggregates are small, amorphous protein accumulations. These cellular seeding models replicate aspects of the patient pathological diversity and will be a useful tool in the quest for subtype-specific therapeutics
Effect of the harvest date, calcium and other chemicals on the quality and storability of ‘Golden Smoothie’ apples
Apples cultivated in Mexico generally are smaller and softer than those produced in other geographical latitudes considered as optimal for apple production. The aim of this evaluation was determine the effect of applications with calcium, nitrogen, potassium, magnesium, sulfur and naphthaleneacetic acid (NAA), as well as the harvest date on the quality of apple fruits. ‘Golden Smoothie’ apple trees were treated foliarly with CaCl2 with and without NAA, and with a mixture of N, K, Mg and S or gypsum applied to soil for two years. Apples were harvested at 141 (regular harvest date), 161 (mid-late harvest) and 171 days (late harvest) after full bloom (DAFB) and evaluated for quality at harvest time and during their storage at 0°C for up to 179 days. Foliar applications of CaCl2 significantly increased the calcium content in fruit and leaves, but fruit quality, including firmness, was not influenced. Fertilization of soil with the mixture of nutrients, including CaSO4, did not influence the fruit quality. Lately harvested fruit was 14.9% heavier but 17.1% softer than fruit picked at the commercial harvest date. Delaying of fruit harvest reduced about 43 d the storability of fruit. Based in these results, the relative softness of apples grown in Mexico is not related with its calcium content, hence unlikely to be overcome with the application of this mineral. Even in the control fruits, both seasons, the stored fruits do not show some physiological disorder as bitter pit.
Objective: Apples cultivated in Mexico generally are smaller and softer than those produced in other geographical latitudes considered as optimal for apple production. The aim of this evaluation was determine the effect of applications with calcium, nitrogen, potassium, magnesium, sulfur and naphthaleneacetic acid (NAA), as well as the harvest date on the quality of apple fruits. Methodology ‘Golden Smoothie’ apple trees were treated foliarly with CaCl2 with and without NAA, and with a mixture of N, K, Mg and S or gypsum applied to soil for two years. Apples were harvested at 141 (regular harvest date), 161 (mid-late harvest) and 171 days (late harvest) after full bloom (DAFB) and evaluated for quality at harvest time and during their storage at 0°C for up to 179 days. Results: Foliar applications of CaCl2 significantly increased the calcium content in fruit and leaves, but fruit quality, including firmness, was not influenced. Fertilization of soil with the mixture of nutrients, including CaSO4, did not influence the fruit quality. Lately harvested fruit was 14.9% heavier but 17.1% softer than fruit picked at the commercial harvest date. Delaying of fruit harvest reduced about 43 d the storability of fruit. Based in these results, the relative softness of apples grown in Mexico is not related with its calcium content, hence unlikely to be overcome with the application of this mineral. Conclusions: Even in the control fruits, both seasons, the stored fruits do not show some physiological disorder as bitter pi
Genomic Regions Associated with Multiple Sclerosis Are Active in B Cells
More than 50 genomic regions have now been shown to influence the risk of multiple sclerosis (MS). However, the mechanisms of action, and the cell types in which these associated variants act at the molecular level remain largely unknown. This is especially true for associated regions containing no known genes. Given the evidence for a role for B cells in MS, we hypothesized that MS associated genomic regions co-localized with regions which are functionally active in B cells. We used publicly available data on 1) MS associated regions and single nucleotide polymorphisms (SNPs) and 2) chromatin profiling in B cells as well as three additional cell types thought to be unrelated to MS (hepatocytes, fibroblasts and keratinocytes). Genomic intervals and SNPs were tested for overlap using the Genomic Hyperbrowser. We found that MS associated regions are significantly enriched in strong enhancer, active promoter and strong transcribed regions (p = 0.00005) and that this overlap is significantly higher in B cells than control cells. In addition, MS associated SNPs also land in active promoter (p = 0.00005) and enhancer regions more than expected by chance (strong enhancer p = 0.0006; weak enhancer p = 0.00005). These results confirm the important role of the immune system and specifically B cells in MS and suggest that MS risk variants exert a gene regulatory role. Previous studies assessing MS risk variants in T cells may be missing important effects in B cells. Similar analyses in other immunological cell types relevant to MS and functional studies are necessary to fully elucidate how genes contribute to MS pathogenesis
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