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• W66296548 abstract "Mutations as sources of evolution have long been the focus of attention in thebiomedical literature. Accessing the mutational information and their impactson protein properties facilitates research in various domains, such asenzymology and pharmacology. However, manually reading through the rich and fast growing repositoryof biomedical literature is expensive and time-consuming. A number of manually curateddatabases, such as BRENDA (http://www.brenda-enzymes.org), try to index and provide thisinformation; yet the provided data seems to be incomplete. Thus, there is agrowing need for automated approaches to extract this information.In this work, we present a system to automatically extract and summarize impactinformation from protein mutations.Our system extraction module is split into subtasks: organism analysis,mutation detection, protein property extraction and impactanalysis. Organisms, as sources of proteins, are required to be extracted tohelp disambiguation of genes and proteins. Thus, our system extracts andgrounds organisms to NCBI. We detect mutation series to correctly ground our detectedimpacts. Our system also extracts the affected protein properties as well as the magnitude of theeffects.The output of our system is populated to an OWL-DL ontology, which can then be queried to provide structured information. The performance of the system is evaluated on both external and internal corpora and databases. The results show the reliability of the approaches. Our Organism extraction system achieves a precision and recall of 95%and 94% and a grounding accuracy of 97.5% on the OT corpus. On the manuallyannotated corpus of Linneaus-100, the results show a precision and recall of99% and 97% and grounding with an accuracy of 97.4%.In the impact detection task, our system achieves a precision and recall of70.4%-71.8% and 71.2%-71.3% on a manually annotated documents. Our system grounds the detectedimpacts with an accuracy of 70.1%-71.7% on the manually annotated documentsand a precision and recall of 57%-57.5% and 82.5%-84.2% against the BRENDA data." @default.
• W66296548 created "2016-06-24" @default.
• W66296548 creator A5069421871 @default.
• W66296548 date "2011-09-12" @default.
• W66296548 modified "2023-09-23" @default.
• W66296548 title "Automated Extraction of Protein Mutation Impacts from the Biomedical Literature" @default.
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