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Text Mining Protocol to Retrieve Significant Drug–Gene Interactions from PubMed Abstracts

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Biomedical Text Mining

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2496))

Abstract

Genes and proteins form the basis of all cellular processes and ensure a smooth functioning of the human system. The diseases caused in humans can be either genetic in nature or may be caused due to external factors. Genetic diseases are mainly the result of any anomaly in gene/protein structure or function. This disruption interferes with the normal expression of cellular components. Against external factors, even though the immunogenicity of every individual protects them to a certain extent from infections, they are still susceptible to other disease-causing agents. Understanding the biological pathway/entities that could be targeted by specific drugs is an essential component of drug discovery. The traditional drug target discovery process is time-consuming and practically not feasible. A computational approach could provide speed and efficiency to the method. With the presence of vast biomedical literature, text mining also seems to be an obvious choice which could efficiently aid with other computational methods in identifying drug–gene targets. These could aid in initial stages of reviewing the disease components or can even aid parallel in extracting drug–disease–gene/protein relationships from literature. The present chapter aims at finding drug–gene interactions and how the information could be explored for drug interaction.

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Author information

Author notes

  1. Oviya Ramalakshmi Iyyappan and Sharanya Manoharan contributed equally to this work.

Authors and Affiliations

  1. Department of Biomedical Engineering, PSG College of Technology, Coimbatore, Tamilnadu, India

    Sadhanha Anand

  2. Department of Sciences, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Chennai, Tamilnadu, India

    Oviya Ramalakshmi Iyyappan

  3. Department of Bioinformatics, Stella Maris College (Autonomous), Chennai, Tamilnadu, India

    Sharanya Manoharan

  4. Department of Pharmacology, Cheran College of Pharmacy, Coimbatore, Tamilnadu, India

    Dheepa Anand

  5. Department of Drugs Control, Govt. of Tamil Nadu, Tirunelveli, Tamilnadu, India

    Manonmani Alvin Jose

  6. International Business Unit, Alembic Pharmaceuticals Limited, Vadodara, Gujarat, India

    Raja Ravi Shanker

Authors
  1. Sadhanha Anand
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  2. Oviya Ramalakshmi Iyyappan
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  3. Sharanya Manoharan
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  4. Dheepa Anand
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  5. Manonmani Alvin Jose
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  6. Raja Ravi Shanker
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Editor information

Editors and Affiliations

  1. Morgridge Institute for Research, University of Wisconsin, Madison, WI, USA

    Kalpana Raja

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© 2022 The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature

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Anand, S., Iyyappan, O.R., Manoharan, S., Anand, D., Jose, M.A., Shanker, R.R. (2022). Text Mining Protocol to Retrieve Significant Drug–Gene Interactions from PubMed Abstracts. In: Raja, K. (eds) Biomedical Text Mining. Methods in Molecular Biology, vol 2496. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2305-3_2

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  • DOI: https://doi.org/10.1007/978-1-0716-2305-3_2

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-2304-6

  • Online ISBN: 978-1-0716-2305-3

  • eBook Packages: Springer Protocols

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