Identification of Proteins and Genes Associated with Hedgehog Signaling Pathway Involved in Neoplasm Formation Using Text-Mining Approach
Analysis of molecular mechanisms that lead to the development of various types of tumors is essential for biology and medicine, because it may help to find new therapeutic opportunities for cancer treatment and cure including personalized treatment approaches. One of the pathways known to be importa...
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| Format: | Article |
| Language: | English |
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Tsinghua University Press
2024-03-01
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| Series: | Big Data Mining and Analytics |
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| Online Access: | https://www.sciopen.com/article/10.26599/BDMA.2023.9020007 |
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| author | Nadezhda Yu. Biziukova Sergey M. Ivanov Olga A. Tarasova |
| author_facet | Nadezhda Yu. Biziukova Sergey M. Ivanov Olga A. Tarasova |
| author_sort | Nadezhda Yu. Biziukova |
| collection | DOAJ |
| description | Analysis of molecular mechanisms that lead to the development of various types of tumors is essential for biology and medicine, because it may help to find new therapeutic opportunities for cancer treatment and cure including personalized treatment approaches. One of the pathways known to be important for the development of neoplastic diseases and pathological processes is the Hedgehog signaling pathway that normally controls human embryonic development. Systematic accumulation of various types of biological data, including interactions between proteins, regulation of genes transcription, proteomics, and metabolomics experiments results, allows the application of computational analysis of these big data for identification of key molecular mechanisms of certain diseases and pathologies and promising therapeutic targets. The aim of this study is to develop a computational approach for revealing associations between human proteins and genes interacting with the Hedgehog pathway components, as well as for identifying their roles in the development of various types of tumors. We automatically collect sets of abstract texts from the NCBI PubMed bibliographic database. For recognition of the Hedgehog pathway proteins and genes and neoplastic diseases we use a dictionary-based named entity recognition approach, while for all other proteins and genes machine learning method is used. For association extraction, we develop a set of semantic rules. We complete the results of the text analysis with the gene set enrichment analysis. The identified key pathways that may influence the Hedgehog pathway and their roles in tumor development are then verified using the information in the literature. |
| format | Article |
| id | doaj-art-ff80b30a7c7f43b4958a3c8283f68e02 |
| institution | Kabale University |
| issn | 2096-0654 |
| language | English |
| publishDate | 2024-03-01 |
| publisher | Tsinghua University Press |
| record_format | Article |
| series | Big Data Mining and Analytics |
| spelling | doaj-art-ff80b30a7c7f43b4958a3c8283f68e022025-02-03T00:17:03ZengTsinghua University PressBig Data Mining and Analytics2096-06542024-03-017110713010.26599/BDMA.2023.9020007Identification of Proteins and Genes Associated with Hedgehog Signaling Pathway Involved in Neoplasm Formation Using Text-Mining ApproachNadezhda Yu. Biziukova0Sergey M. Ivanov1Olga A. Tarasova2Department of Bioinformatics, Institute of Biomedical Chemistry, Moscow 119121, RussiaDepartment of Bioinformatics, Institute of Biomedical Chemistry, Moscow 119121, Russia, and also with Department of Bioinformatics, Pirogov Russian National Research Medical University, Moscow 117997, RussiaDepartment of Bioinformatics, Institute of Biomedical Chemistry, Moscow 119121, RussiaAnalysis of molecular mechanisms that lead to the development of various types of tumors is essential for biology and medicine, because it may help to find new therapeutic opportunities for cancer treatment and cure including personalized treatment approaches. One of the pathways known to be important for the development of neoplastic diseases and pathological processes is the Hedgehog signaling pathway that normally controls human embryonic development. Systematic accumulation of various types of biological data, including interactions between proteins, regulation of genes transcription, proteomics, and metabolomics experiments results, allows the application of computational analysis of these big data for identification of key molecular mechanisms of certain diseases and pathologies and promising therapeutic targets. The aim of this study is to develop a computational approach for revealing associations between human proteins and genes interacting with the Hedgehog pathway components, as well as for identifying their roles in the development of various types of tumors. We automatically collect sets of abstract texts from the NCBI PubMed bibliographic database. For recognition of the Hedgehog pathway proteins and genes and neoplastic diseases we use a dictionary-based named entity recognition approach, while for all other proteins and genes machine learning method is used. For association extraction, we develop a set of semantic rules. We complete the results of the text analysis with the gene set enrichment analysis. The identified key pathways that may influence the Hedgehog pathway and their roles in tumor development are then verified using the information in the literature.https://www.sciopen.com/article/10.26599/BDMA.2023.9020007text-miningdata mininghedgehog pathwayneoplastic processesenrichment analysispathology molecular mechanisms |
| spellingShingle | Nadezhda Yu. Biziukova Sergey M. Ivanov Olga A. Tarasova Identification of Proteins and Genes Associated with Hedgehog Signaling Pathway Involved in Neoplasm Formation Using Text-Mining Approach Big Data Mining and Analytics text-mining data mining hedgehog pathway neoplastic processes enrichment analysis pathology molecular mechanisms |
| title | Identification of Proteins and Genes Associated with Hedgehog Signaling Pathway Involved in Neoplasm Formation Using Text-Mining Approach |
| title_full | Identification of Proteins and Genes Associated with Hedgehog Signaling Pathway Involved in Neoplasm Formation Using Text-Mining Approach |
| title_fullStr | Identification of Proteins and Genes Associated with Hedgehog Signaling Pathway Involved in Neoplasm Formation Using Text-Mining Approach |
| title_full_unstemmed | Identification of Proteins and Genes Associated with Hedgehog Signaling Pathway Involved in Neoplasm Formation Using Text-Mining Approach |
| title_short | Identification of Proteins and Genes Associated with Hedgehog Signaling Pathway Involved in Neoplasm Formation Using Text-Mining Approach |
| title_sort | identification of proteins and genes associated with hedgehog signaling pathway involved in neoplasm formation using text mining approach |
| topic | text-mining data mining hedgehog pathway neoplastic processes enrichment analysis pathology molecular mechanisms |
| url | https://www.sciopen.com/article/10.26599/BDMA.2023.9020007 |
| work_keys_str_mv | AT nadezhdayubiziukova identificationofproteinsandgenesassociatedwithhedgehogsignalingpathwayinvolvedinneoplasmformationusingtextminingapproach AT sergeymivanov identificationofproteinsandgenesassociatedwithhedgehogsignalingpathwayinvolvedinneoplasmformationusingtextminingapproach AT olgaatarasova identificationofproteinsandgenesassociatedwithhedgehogsignalingpathwayinvolvedinneoplasmformationusingtextminingapproach |