OpenAIRE Graph: status & enrichments via the SciLake project

Slides describing SciLake activities on extending the OpenAIRE Graph. The presentation was made during the OSFair 2023

BIP! NDR (NoDoiRefs): A Dataset of Citations From Papers Without DOIs in Computer Science Conferences and Workshops

In the field of Computer Science, conference and workshop papers serve as important contributions, carrying substantial weight in research assessment processes, compared to other disciplines. However, a considerable number of these papers are not assigned a Digital Object Identifier (DOI), hence their citations are not reported in widely used citation datasets like OpenCitations and Crossref, raising limitations to citation analysis. While the Microsoft Academic Graph (MAG) previously addressed this issue by providing substantial coverage, its discontinuation has created a void in available data. BIP! NDR aims to alleviate this issue and enhance the research assessment processes within the field of Computer Science. To accomplish this, it leverages a workflow that identifies and retrieves Open Science papers lacking DOIs from the DBLP Corpus, and by performing text analysis, it extracts citation information directly from their full text. The current version of the dataset contains more than 510K citations made by approximately 60K open access Computer Science conference or workshop papers that, according to DBLP, do not have a DOI

TarBase 6.0: capturing the exponential growth of miRNA targets with experimental support

As the relevant literature and the number of experiments increase at a super linear rate, databases that curate and collect experimentally verified microRNA (miRNA) targets have gradually emerged. These databases attempt to provide efficient access to this wealth of experimental data, which is scattered in thousands of manuscripts. Aim of TarBase 6.0 (http://www.microrna.gr/tarbase) is to face this challenge by providing a significant increase of available miRNA targets derived from all contemporary experimental techniques (gene specific and high-throughput), while incorporating a powerful set of tools in a user-friendly interface. TarBase 6.0 hosts detailed information for each miRNA–gene interaction, ranging from miRNA- and gene-related facts to information specific to their interaction, the experimental validation methodologies and their outcomes. All database entries are enriched with function-related data, as well as general information derived from external databases such as UniProt, Ensembl and RefSeq. DIANA microT miRNA target prediction scores and the relevant prediction details are available for each interaction. TarBase 6.0 hosts the largest collection of manually curated experimentally validated miRNA–gene interactions (more than 65 000 targets), presenting a 16.5–175-fold increase over other available manually curated databases

DIANA-microT Web server upgrade supports Fly and Worm miRNA target prediction and bibliographic miRNA to disease association

microRNAs (miRNAs) are small endogenous RNA molecules that are implicated in many biological processes through post-transcriptional regulation of gene expression. The DIANA-microT Web server provides a user-friendly interface for comprehensive computational analysis of miRNA targets in human and mouse. The server has now been extended to support predictions for two widely studied species: Drosophila melanogaster and Caenorhabditis elegans. In the updated version, the Web server enables the association of miRNAs to diseases through bibliographic analysis and provides insights for the potential involvement of miRNAs in biological processes. The nomenclature used to describe mature miRNAs along different miRBase versions has been extensively analyzed, and the naming history of each miRNA has been extracted. This enables the identification of miRNA publications regardless of possible nomenclature changes. User interaction has been further refined allowing users to save results that they wish to analyze further. A connection to the UCSC genome browser is now provided, enabling users to easily preview predicted binding sites in comparison to a wide array of genomic tracks, such as single nucleotide polymorphisms. The Web server is publicly accessible in www.microrna.gr/microT-v4

One Decade of Development and Evolution of MicroRNA Target Prediction Algorithms

Nearly two decades have passed since the publication of the first study reporting the discovery of microRNAs (miRNAs). The key role of miRNAs in post-transcriptional gene regulation led to the performance of an increasing number of studies focusing on origins, mechanisms of action and functionality of miRNAs. In order to associate each miRNA to a specific functionality it is essential to unveil the rules that govern miRNA action. Despite the fact that there has been significant improvement exposing structural characteristics of the miRNA-mRNA interaction, the entire physical mechanism is not yet fully understood. In this respect, the development of computational algorithms for miRNA target prediction becomes increasingly important. This manuscript summarizes the research done on miRNA target prediction. It describes the experimental data currently available and used in the field and presents three lines of computational approaches for target prediction. Finally, the authors put forward a number of considerations regarding current challenges and future direction

miRGen 2.0: a database of microRNA genomic information and regulation

MicroRNAs are small, non-protein coding RNA molecules known to regulate the expression of genes by binding to the 3′UTR region of mRNAs. MicroRNAs are produced from longer transcripts which can code for more than one mature miRNAs. miRGen 2.0 is a database that aims to provide comprehensive information about the position of human and mouse microRNA coding transcripts and their regulation by transcription factors, including a unique compilation of both predicted and experimentally supported data. Expression profiles of microRNAs in several tissues and cell lines, single nucleotide polymorphism locations, microRNA target prediction on protein coding genes and mapping of miRNA targets of co-regulated miRNAs on biological pathways are also integrated into the database and user interface. The miRGen database will be continuously maintained and freely available at http://www.microrna.gr/mirgen/

DIANA-microT web server: elucidating microRNA functions through target prediction

Computational microRNA (miRNA) target prediction is one of the key means for deciphering the role of miRNAs in development and disease. Here, we present the DIANA-microT web server as the user interface to the DIANA-microT 3.0 miRNA target prediction algorithm. The web server provides extensive information for predicted miRNA:target gene interactions with a user-friendly interface, providing extensive connectivity to online biological resources. Target gene and miRNA functions may be elucidated through automated bibliographic searches and functional information is accessible through Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The web server offers links to nomenclature, sequence and protein databases, and users are facilitated by being able to search for targeted genes using different nomenclatures or functional features, such as the genes possible involvement in biological pathways. The target prediction algorithm supports parameters calculated individually for each miRNA:target gene interaction and provides a signal-to-noise ratio and a precision score that helps in the evaluation of the significance of the predicted results. Using a set of miRNA targets recently identified through the pSILAC method, the performance of several computational target prediction programs was assessed. DIANA-microT 3.0 achieved there with 66% the highest ratio of correctly predicted targets over all predicted targets. The DIANA-microT web server is freely available at www.microrna.gr/microT