BioHackathon series in 2011 and 2012: penetration of ontology and linked data in life science domains

The application of semantic technologies to the integration of biological data and the interoperability of bioinformatics analysis and visualization tools has been the common theme of a series of annual BioHackathons hosted in Japan for the past five years. Here we provide a review of the activities and outcomes from the BioHackathons held in 2011 in Kyoto and 2012 in Toyama. In order to efficiently implement semantic technologies in the life sciences, participants formed various sub-groups and worked on the following topics: Resource Description Framework (RDF) models for specific domains, text mining of the literature, ontology development, essential metadata for biological databases, platforms to enable efficient Semantic Web technology development and interoperability, and the development of applications for Semantic Web data. In this review, we briefly introduce the themes covered by these sub-groups. The observations made, conclusions drawn, and software development projects that emerged from these activities are discussed

Additional file 1: of Colil: a database and search service for citation contexts in the life sciences domain

Retrieving sets of citation contexts for papers with PubMed ID 18996891, 21071411, 22135297, and 23376192. (XLSX 66 kb

Identifying disease-phenotype associations using PubAnnotation and PubDictionaries for supporting diagnosis of intractable diseases

Presentation for BLAH4 symposium<div>http://blah4.linkedannotation.org/program<br></div

PubCaseFinder: A diagnosis assistant system for rare diseases using disease-phenotype associations from published case reports

<div>ISBC3, 20 Jan 2018</div><div>PubCaseFinder: A diagnosis assistant system for rare diseases using disease-phenotype associations from published case reports<br></div

PubCaseFinder: A diagnosis assistant system for rare diseases using published case reports

Lightning talk slides for BioHackathon1

miRNA-target prediction based on transcriptional regulation

<p>Abstract</p> <p>Background</p> <p>microRNAs (miRNAs) are tiny endogenous RNAs that have been discovered in animals and plants, and direct the post-transcriptional regulation of target mRNAs for degradation or translational repression via binding to the 3'UTRs and the coding exons. To gain insight into the biological role of miRNAs, it is essential to identify the full repertoire of mRNA targets (target genes). A number of computer programs have been developed for miRNA-target prediction. These programs essentially focus on potential binding sites in 3'UTRs, which are recognized by miRNAs according to specific base-pairing rules.</p> <p>Results</p> <p>Here, we introduce a novel method for miRNA-target prediction that is entirely independent of existing approaches. The method is based on the hypothesis that transcription of a miRNA and its target genes tend to be co-regulated by common transcription factors. This hypothesis predicts the frequent occurrence of common <it>cis</it>-elements between promoters of a miRNA and its target genes. That is, our proposed method first identifies putative <it>cis</it>-elements in a promoter of a given miRNA, and then identifies genes that contain common putative <it>cis</it>-elements in their promoters. In this paper, we show that a significant number of common <it>cis</it>-elements occur in ~28% of experimentally supported human miRNA-target data. Moreover, we show that the prediction of human miRNA-targets based on our method is statistically significant. Further, we discuss the random incidence of common <it>cis</it>-elements, their consensus sequences, and the advantages and disadvantages of our method.</p> <p>Conclusions</p> <p>This is the first report indicating prevalence of transcriptional regulation of a miRNA and its target genes by common transcription factors and the predictive ability of miRNA-targets based on this property.</p