title: IBDsite: a Galaxy-interacting, integrative database for supporting inflammatory bowel disease high throughput data analysis.
abstract: BACKGROUND
  Inflammatory bowel diseases (IBD) refer to a group of inflammatory conditions concerning colon and small intestine, which cause socially uncomfortable symptoms and often are associated with an increased risk of colon cancer. IBD are complex disorders, which rely on genetic susceptibility, environmental factors, deregulation of the immune system, and host relationship with commensal microbiota. The complexity of these pathologies makes difficult to clearly understand the mechanisms of their onset. Therefore, the study of IBD must be faced exploiting an integrated and multilevel approach, ranging from genes, transcripts and proteins to pathways altered in affected tissues, and carefully considering their regulatory mechanisms, which may intervene in the pathology onset. It is also crucial to have a knowledge base about the symbiotic bacteria that are hosted in the human gut. To date, much data exist regarding IBD and human commensal bacteria, but this information is sparse in literature and no free resource provides a homogeneously and rationally integrated view of biomolecular data related to these pathologies.
  
  
  METHODS
  Human genes altered in IBD have been collected from literature, paying particular interest for the immune system alterations prompted by the interaction with the gut microbiome. This process has been performed manually to assure the reliability of collected data. Heterogeneous metadata from different sources have been automatically formatted and integrated in order to enrich information about these altered genes. A user-friendly web interface has been created for easy access to structured data. Tools such as gene clustering coefficients, all-pairs shortest paths and pathway lengths calculation have been developed to provide data analysis support. Moreover, the implemented resource is compliant to the Galaxy framework, allowing the collected data to be exploited in the context of high throughput bioinformatics analysis.
  
  
  RESULTS
  To fill the lack of a reference resource for 'omics' science analysis in the context of IBD, we developed the IBDsite (available at http://www.itb.cnr.it/ibd), a disease-oriented platform, which collects data related to biomolecular mechanisms involved in the IBD onset. The resource provides a section devoted to human genes identified as altered in IBD, which can be queried at different biomolecular levels and visualised in gene-centred report pages. Furthermore, the system presents information related to the gut microbiota involved in IBD affected patients. The IBDsite is compliant with all Galaxy installations (in particular, it can be accessed from our custom version of Galaxy, http://www.itb.cnr.it/galaxy), in order to facilitate high-throughput data integration and to enable evaluations of the genomic basis of these diseases, complementing the tools embedded in the IBDsite.
  
  
  CONCLUSIONS
  Lots of sparse data exist concerning IBD studies, but no on-line resource homogeneously and rationally integrate and collect them. The IBDsite is an attempt to group available information regarding human genes and microbial aspects related to IBD, by means of a multilevel mining tool. Moreover, it constitutes a knowledge base to filter, annotate and understand new experimental data in order to formulate new scientific hypotheses, thanks to the possibility of integrating genomics aspects by employing the Galaxy framework. Discussed use-cases demonstrate that the developed system is useful to infer not trivial knowledge from the existing widespread data or from novel experiments.
authors.affiliation: Institute for Biomedical Technologies, National Research Council, Via Fratelli Cervi, 93, Segrate (Mi), Italy. ivan.merelli@itb.cnr.it
authors.forename: I
authors.initials: I
authors.lastname: Merelli
authors.forename: F
authors.initials: F
authors.lastname: Viti
authors.forename: L
authors.initials: L
authors.lastname: Milanesi
mesh_terms: D003106:Colon / Q000378:metabolism / Q000382:microbiology / Q000473:pathology; D030541:Databases, Genetic; D006801:Humans; D015212:Inflammatory Bowel Diseases / Q000235:genetics* / Q000276:immunology / Q000382:microbiology / Q000473:pathology*; D020407:Internet; D007421:Intestine, Small / Q000378:metabolism / Q000382:microbiology / Q000473:pathology; D054892:Metagenome; D020411:Oligonucleotide Array Sequence Analysis; D015203:Reproducibility of Results; D017423:Sequence Analysis, RNA; D012984:Software