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Text Mining in Biological data for Protein-Protein Interaction

Taheri, Nooshin | 2016

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  1. Type of Document: M.Sc. Thesis
  2. Language: English
  3. Document No: 49292 (52)
  4. University: Sharif University of Technology, International Campus, Kish Island
  5. Department: Science and Engineering
  6. Advisor(s): Ghorshi, Ali; Kavousi, Kaveh
  7. Abstract:
  8. Decades ago, scientists and researchers found out proteins are not function isolated and act in multi protein complexes as complex networks. So, they started to study about proteins and their interaction in the term of protein-protein interaction, therefore, the number of publication in this field grows rapidly. This large amount of published articles (in scientific journals or web pages or books) are unstructured and it is hard to classify them manually. Also, study and read all of these documents is difficult for one person. Hence, it’s better to find a way which could help scientists and researcher to study these unstructured or semi-structured information more easily. The best way to classify the unstructured or semi-structured data is text mining.. The text mining technique which used for finding interaction between pair of proteins is called “text mining for protein-protein interactions”. In this thesis, we introduce an application which we call it “NLPPI Miner”, which uses Natural Language and Machine language techniques such as regex to find protein-protein interactions. The result shows that NLPPI Miner can predict some interactions, which are not in the benchmark dataset
  9. Keywords:
  10. Text Mining ; Natural Language Processing ; Machine Learning ; Protein-Protein Interaction ; Bioloical Data

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