Literature mining and network analysis in Biology

Postgraduate Thesis uoadl:2961690 130 Read counter

Unit:
Specialty Molecular Biomedicine Mechanisms of Disease, Molecular and Cellular Therapies, and Bioinnovation
Library of the School of Health Sciences
Deposit date:
2021-10-05
Year:
2021
Author:
Zafeiropoulou Sofia
Supervisors info:
Γεώργιος Α. Παυλόπουλος, Ερευνητής Β΄, Ερευνητικό Κέντρο Βιοϊατρικών Επιστημών «Αλέξανδρος Φλέμινγκ»
Χριστόφορος Νικολάου, Ερευνητής Β΄, Ερευνητικό Κέντρο Βιοϊατρικών Επιστημών «Αλέξανδρος Φλέμινγκ»
Γεώργιος Κόλλιας, Καθηγητής, Ιατρική Σχολή, ΕΚΠΑ
Original Title:
Literature mining and network analysis in Biology
Languages:
English
Translated title:
Literature mining and network analysis in Biology
Summary:
The particular thesis presents OnTheFly2.0, a web-based, versatile tool dedicated to the extraction and subsequent analysis of biomedical terms from individual files. More specifically, OnTheFly2.0 supports different file formats, enabling simultaneous file handling. The integration of the EXTRACT tagging service allows the implementation of Named Entity Recognition (NER) for genes/proteins, chemical compounds, organisms, tissues, environments, diseases, phenotypes and Gene Ontology terms, as well as the generation of popup windows which provide concise, context related information about the identified term, accompanied by links to various databases. Once named entities, such as proteins, genes and chemicals are identified, they can be further explored via functional and publication enrichment analysis or be associated with diseases and protein domains reporting from protein family databases. Finally, visualization of protein-protein and protein-chemical associations is possible through the generation of interactive networks from the STRING and STITCH services, respectively. OnTheFly2.0 currently supports 197 species and is available at http://onthefly.pavlopouloslab.info.
Main subject category:
Health Sciences
Keywords:
Automated knowledge extraction, Named Entity Recognition, Enrichment analysis, Network analysis
Index:
No
Number of index pages:
0
Contains images:
Yes
Number of references:
260
Number of pages:
95
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