Biomedical Text Mining

Buch | Softcover

321 Seiten

2023 | 1st ed. 2022
Springer-Verlag New York Inc.
978-1-0716-2307-7 (ISBN)

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lt;p>This volume details step-by-step instructions on biomedical literature mining protocols. Chapters guide readers through various topics such as, disease comorbidity, literature-based discovery, protocols to combine literature mining, machine learning for predicting biomedical discoveries, and uncovering unknown public knowledge by combining two pieces of information from different sets of PubMed articles. Additional chapters discuss the importance of data science to understand outbreaks such as COVID-19. Written in the format of the highly successful Methods in Molecular Biology series, each chapter includes an introduction to the topic, lists necessary materials and reagents, includes tips on troubleshooting and known pitfalls, and step-by-step, readily reproducible protocols.

Authoritative and cutting-edge, Biomedical Text Mining aims to be a useful practical guide to researches to help further their studies.

lt;p>1. Biomedical literature mining and its components

Kalpana Raja

2. Text mining protocol to retrieve significant drug-gene interactions from PubMed abstracts

Sadhanha Anand, Oviya Ramalakshmi Iyyappan, Sharanya Manoharan, Dheepa Anand, Manonmani Alvin Jose, and Raja Ravi Shankar

3. A hybrid protocol for finding novel gene targets for various diseases using microarray expression data analysis and text mining

Sharanya Manoharan and Oviya Ramalakshmi Iyyappan

4. Finding gene associations by text mining and annotating it with Gene Ontology

Oviya Ramalakshmi Iyyappan and Sharanya Manoharan

5. Biomedical literature mining for repurposing laboratory tests

Finn Kuusisto, Ross Kleiman, and Jeremy Weiss

6. A simple computational approach to identify potential drugs for multiple sclerosis and cognitive disorders from expert curated resources

Kalpana Raja, Archana Prabahar, and Shyam Sundar Arputhanatham

7. Combining literature mining and machine learning for predicting biomedical discoveries

Balu Bhasuran

8. A Text Mining Protocol for Mining Biological Pathways and Regulatory Networks from Biomedical Literature

Sabenabanu Abdulkadhar and Jeyakumar Natarajan

9. Text mining and machine learning protocol for extracting human related protein phosphorylation information from PubMed

Krishnamurthy Arumugam and Raja Ravi Shankar

10. A text mining and machine learning protocol for extracting post translational modifications of proteins from PubMed: A special focus on glycosylation, acetylation, methylation, hydroxylation, and ubiquitination

Krishnamurthy Arumugam, Malathi Sellappan, Dheepa Anand, Sadhanha Anand, and Subhashini Vedagiri Radhakishnan

11. A hybrid protocol for identifying comorbidity-based potential drugs for COVID-19 using biomedical literature mining, network analysis, and deep learning

Archana Prabahar and Anbumathi Palanisamy

12. BioBERT and Similar Approaches for Relation Extraction

Balu Bhasuran

13. A text mining protocol for predicting drug-drug interaction and adverse drug reactions from PubMed articles

Mohamed Saleem Abdul Shukkoor, Kalpana Raja, and Mohamad Taufik Hidayat Bin Baharuldin

14. A text mining protocol for extracting drug-drug interaction and adverse drug reactions specific to patient population, pharmacokinetics, pharmacodynamics, and disease

Mohamed Saleem Abdul Shukkoor, Mohamad Taufik Hidayat Bin Baharuldin, and Kalpana Raja

15. Extracting significant comorbid diseases from MeSH index of PubMed

Dheepa Anand, Sharanya Manoharan, Oviya Ramalakshmi Iyyappan, Sadhanha Anand, and Kalpana Raja

16. Integration of transcriptomic data and metabolomic data using biomedical literature mining and pathway analysis

Archana Prabahar

Erscheinungsdatum	21.06.2023
Reihe/Serie	Methods in Molecular Biology
Zusatzinfo	76 Illustrations, color; 3 Illustrations, black and white; XI, 321 p. 79 illus., 76 illus. in color.
Verlagsort	New York, NY
Sprache	englisch
Maße	178 x 254 mm
Themenwelt	Mathematik / Informatik ► Informatik ► Theorie / Studium
	Informatik ► Weitere Themen ► Bioinformatik
	Medizin / Pharmazie ► Medizinische Fachgebiete ► Biomedizin
	Naturwissenschaften ► Biologie ► Genetik / Molekularbiologie
Schlagworte	BioBert • Drug-drug interaction • gene expression omnibus • Metabolomics • Transcriptomics
ISBN-10	1-0716-2307-9 / 1071623079
ISBN-13	978-1-0716-2307-7 / 9781071623077
Zustand	Neuware