TY - JOUR
T1 - OnTheFly2.0
T2 - a text-mining web application for automated biomedical entity recognition, document annotation, network and functional enrichment analysis
AU - Baltoumas, Fotis A
AU - Zafeiropoulou, Sofia
AU - Karatzas, Evangelos
AU - Paragkamian, Savvas
AU - Thanati, Foteini
AU - Iliopoulos, Ioannis
AU - Eliopoulos, Aristides G
AU - Schneider, Reinhard
AU - Jensen, Lars Juhl
AU - Pafilis, Evangelos
AU - Pavlopoulos, Georgios A
N1 - © The Author(s) 2021. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics.
PY - 2021
Y1 - 2021
N2 - Extracting and processing information from documents is of great importance as lots of experimental results and findings are stored in local files. Therefore, extracting and analyzing biomedical terms from such files in an automated way is absolutely necessary. In this article, we present OnTheFly2.0, a web application for extracting biomedical entities from individual files such as plain texts, office documents, PDF files or images. OnTheFly2.0 can generate informative summaries in popup windows containing knowledge related to the identified terms along with links to various databases. It uses the EXTRACT tagging service to perform named entity recognition (NER) for genes/proteins, chemical compounds, organisms, tissues, environments, diseases, phenotypes and gene ontology terms. Multiple files can be analyzed, whereas identified terms such as proteins or genes can be explored through functional enrichment analysis or be associated with diseases and PubMed entries. Finally, protein-protein and protein-chemical networks can be generated with the use of STRING and STITCH services. To demonstrate its capacity for knowledge discovery, we interrogated published meta-analyses of clinical biomarkers of severe COVID-19 and uncovered inflammatory and senescence pathways that impact disease pathogenesis. OnTheFly2.0 currently supports 197 species and is available at http://bib.fleming.gr:3838/OnTheFly/ and http://onthefly.pavlopouloslab.info.
AB - Extracting and processing information from documents is of great importance as lots of experimental results and findings are stored in local files. Therefore, extracting and analyzing biomedical terms from such files in an automated way is absolutely necessary. In this article, we present OnTheFly2.0, a web application for extracting biomedical entities from individual files such as plain texts, office documents, PDF files or images. OnTheFly2.0 can generate informative summaries in popup windows containing knowledge related to the identified terms along with links to various databases. It uses the EXTRACT tagging service to perform named entity recognition (NER) for genes/proteins, chemical compounds, organisms, tissues, environments, diseases, phenotypes and gene ontology terms. Multiple files can be analyzed, whereas identified terms such as proteins or genes can be explored through functional enrichment analysis or be associated with diseases and PubMed entries. Finally, protein-protein and protein-chemical networks can be generated with the use of STRING and STITCH services. To demonstrate its capacity for knowledge discovery, we interrogated published meta-analyses of clinical biomarkers of severe COVID-19 and uncovered inflammatory and senescence pathways that impact disease pathogenesis. OnTheFly2.0 currently supports 197 species and is available at http://bib.fleming.gr:3838/OnTheFly/ and http://onthefly.pavlopouloslab.info.
U2 - 10.1093/nargab/lqab090
DO - 10.1093/nargab/lqab090
M3 - Journal article
C2 - 34632381
VL - 3
JO - NAR Genomics and Bioinformatics
JF - NAR Genomics and Bioinformatics
SN - 2631-9268
IS - 4
M1 - lqab090
ER -