Literature DB >> 30848465

Text Mining for Drug Discovery.

Si Zheng1, Shazia Dharssi2, Meng Wu1, Jiao Li1, Zhiyong Lu3.   

Abstract

Recent advances in technology have led to the exponential growth of scientific literature in biomedical sciences. This rapid increase in information has surpassed the threshold for manual curation efforts, necessitating the use of text mining approaches in the field of life sciences. One such application of text mining is in fostering in silico drug discovery such as drug target screening, pharmacogenomics, adverse drug event detection, etc. This chapter serves as an introduction to the applications of various text mining approaches in drug discovery. It is divided into two parts with the first half as an overview of text mining in the biosciences. The second half of the chapter reviews strategies and methods for four unique applications of text mining in drug discovery.

Keywords:  Biomedical literature; Biomedical text mining; Deep learning; Drug discovery; Electronic medical records

Mesh:

Year:  2019        PMID: 30848465     DOI: 10.1007/978-1-4939-9089-4_13

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  10 in total

1.  A Hybrid Protocol for Finding Novel Gene Targets for Various Diseases Using Microarray Expression Data Analysis and Text Mining.

Authors:  Sharanya Manoharan; Oviya Ramalakshmi Iyyappan
Journal:  Methods Mol Biol       Date:  2022

Review 2.  Merging data curation and machine learning to improve nanomedicines.

Authors:  Chen Chen; Zvi Yaari; Elana Apfelbaum; Piotr Grodzinski; Yosi Shamay; Daniel A Heller
Journal:  Adv Drug Deliv Rev       Date:  2022-02-18       Impact factor: 17.873

3.  An automatic hypothesis generation for plausible linkage between xanthium and diabetes.

Authors:  Arida Ferti Syafiandini; Gyuri Song; Yuri Ahn; Heeyoung Kim; Min Song
Journal:  Sci Rep       Date:  2022-10-20       Impact factor: 4.996

Review 4.  How can natural language processing help model informed drug development?: a review.

Authors:  Roopal Bhatnagar; Sakshi Sardar; Maedeh Beheshti; Jagdeep T Podichetty
Journal:  JAMIA Open       Date:  2022-06-11

Review 5.  Computational drug repurposing based on electronic health records: a scoping review.

Authors:  Nansu Zong; Andrew Wen; Sungrim Moon; Sunyang Fu; Liwei Wang; Yiqing Zhao; Yue Yu; Ming Huang; Yanshan Wang; Gang Zheng; Michelle M Mielke; James R Cerhan; Hongfang Liu
Journal:  NPJ Digit Med       Date:  2022-06-14

Review 6.  A Survey on Deep Networks Approaches in Prediction of Sequence-Based Protein-Protein Interactions.

Authors:  Bhawna Mewara; Soniya Lalwani
Journal:  SN Comput Sci       Date:  2022-05-19

Review 7.  Signature-based approaches for informed drug repurposing: targeting CNS disorders.

Authors:  Rammohan Shukla; Nicholas D Henkel; Khaled Alganem; Abdul-Rizaq Hamoud; James Reigle; Rawan S Alnafisah; Hunter M Eby; Ali S Imami; Justin F Creeden; Scott A Miruzzi; Jaroslaw Meller; Robert E Mccullumsmith
Journal:  Neuropsychopharmacology       Date:  2020-06-30       Impact factor: 8.294

8.  Repurposing new drug candidates and identifying crucial molecules underlying PCOS Pathogenesis Based On Bioinformatics Analysis.

Authors:  Zeinab Dehghan; Samira Mohammadi-Yeganeh; Marzieh Sameni; Seyed Amir Mirmotalebisohi; Hakimeh Zali; Mohammad Salehi
Journal:  Daru       Date:  2021-09-04       Impact factor: 3.117

9.  Challenges and opportunities for mining adverse drug reactions: perspectives from pharma, regulatory agencies, healthcare providers and consumers.

Authors:  Graciela Gonzalez-Hernandez; Martin Krallinger; Monica Muñoz; Raul Rodriguez-Esteban; Özlem Uzuner; Lynette Hirschman
Journal:  Database (Oxford)       Date:  2022-09-02       Impact factor: 4.462

10.  Semantic text mining in early drug discovery for type 2 diabetes.

Authors:  Lena K Hansson; Rasmus Borup Hansen; Sune Pletscher-Frankild; Rudolfs Berzins; Daniel Hvidberg Hansen; Dennis Madsen; Sten B Christensen; Malene Revsbech Christiansen; Ulrika Boulund; Xenia Asbæk Wolf; Sonny Kim Kjærulff; Martijn van de Bunt; Søren Tulin; Thomas Skøt Jensen; Rasmus Wernersson; Jan Nygaard Jensen
Journal:  PLoS One       Date:  2020-06-15       Impact factor: 3.240

  10 in total

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