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EnzyMiner: automatic identification of protein level mutations and their impact on target enzymes from PubMed abstracts.

BMC bioinformatics | Aug 27, 2009

BACKGROUND: A better understanding of the mechanisms of an enzyme's functionality and stability, as well as knowledge and impact of mutations is crucial for researchers working with enzymes. Though, several of the enzymes' databases are currently available, scientific literature still remains at large for up-to-date source of learning the effects of a mutation on an enzyme. However, going through vast amounts of scientific documents to extract the information on desired mutation has always been a time consuming process. In this paper, therefore, we describe an unique method, termed as EnzyMiner, which automatically identifies the PubMed abstracts that contain information on the impact of a protein level mutation on the stability and/or the activity of a given enzyme. RESULTS: We present an automated system which identifies the abstracts that contain an amino-acid-level mutation and then classifies them according to the mutation's effect on the enzyme. In the case of mutation identification, MuGeX, an automated mutation-gene extraction system has an accuracy of 93.1% with a 91.5 F-measure. For impact analysis, document classification is performed to identify the abstracts that contain a change in enzyme's stability or activity resulting from the mutation. The system was trained on lipases and tested on amylases with an accuracy of 85%. CONCLUSION: EnzyMiner identifies the abstracts that contain a protein mutation for a given enzyme and checks whether the abstract is related to a disease with the help of information extraction and machine learning techniques. For disease related abstracts, the mutation list and direct links to the abstracts are retrieved from the system and displayed on the Web. For those abstracts that are related to non-diseases, in addition to having the mutation list, the abstracts are also categorized into two groups. These two groups determine whether the mutation has an effect on the enzyme's stability or functionality followed by displaying these on the web.

Pubmed ID: 19758466 RIS Download

Mesh terms: Algorithms | Amino Acid Sequence | Amylases | Computational Biology | Enzymes | Genomics | Information Storage and Retrieval | Lipase | Mutation | Pattern Recognition, Automated | Periodicals as Topic | Proteins | PubMed | Reproducibility of Results

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PubMed

A bibliographic database that provides access to over 22 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites. PubMed citations and abstracts include the fields of biomedicine and health, covering portions of the life sciences, behavioral sciences, chemical sciences, and bioengineering. PubMed also provides access to additional relevant web sites and links to the other NCBI molecular biology resources. Publishers of journals can submit their citations to NCBI and then provide access to the full-text of articles at journal web sites using LinkOut.

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Enzyminer.

EnzyMiner automatically identifies the PubMed abstracts that contain information on the impact of a protein level mutation on the stability or the activity of a given enzyme. For querying EnzyMiner, please choose an enzyme from the list and specify if you are interested in disease related abstracts or non-disease related abstracts. For disease related abstracts, the mutation list and direct links to the abstracts will be displayed. For those abstracts that are related to non-diseases, in addition to having the mutation list, the abstracts are also categorized into two groups. These two groups determine whether the mutation has an effect on the enzyme''s stability or functionality. If your target enzyme is not in the list, please write the enzyme name to the query box. We will run the EnzyMiner for the desired enzyme and add the results to our database. EnzyMiner has been developed by Computational Biology Lab of Sabanci University.

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