Biology subjects

Thanati, F.

Publications and source records attributed to Thanati, F..

2 recordsLinked to original sources

bioRxiv2021

FLAME: a web tool for functional and literature enrichment analysis of multiple gene lists

Functional enrichment is a widely used method for interpreting experimental results by identifying classes of proteins/genes associated with certain biological functions, pathways, diseases or phenotypes. Despite the variety of existing tools, most of them can process a single list per time, thus making a more combinatorial analysis more complicated and prone to errors. In this article, we present FLAME, a web tool for combining multiple lists prior to enrichment analysis. Users can upload several lists of preference and use interactive UpSet plots, as an alternative to Venn diagrams, to handle unions or intersections among the given input files. Functional and literature enrichment along with gene conversions are offered by g:Profiler and aGOtool applications for 197 organisms. In its current version, FLAME can analyze genes/proteins for related articles, Gene Ontologies, pathways, annotations, regulatory motifs, domains, diseases, phenotypes while it can also generate protein-protein interactions derived from STRING. We have herein validated FLAME by interrogating gene expression data associated with the sensitivity of the distal part of the large intestine to experimental colitis-propelled colon cancer. The FLAME application comes with an interactive user-friendly interface which allows easy list manipulation and exploration, while results can be visualized as interactive and parameterizable heatmaps, barcharts, Manhattan plots, networks and tables. AvailabilityFLAME application: http://flame.pavlopouloslab.info Codehttps://github.com/PavlopoulosLab/FLAME

bioinformatics↗

bioRxiv2021

OnTheFly2.0: a text-mining web application for automated biomedical entity recognition, document annotation, network and functional enrichment analysis

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 analysing 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 analysed, 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://onthefly.pavlopouloslab.info.

bioinformatics↗