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Paper   IPM / Biological Sciences / 15338
School of Biological Sciences
  Title:   afpCOOL: A tool for antifreeze protein prediction
1.  Morteza Eslami
2.  Ramin Shirali Hossein Zade
3.  Zeinab Takalloo
4.  Ghasem Mahdevar
5.  Abbasali Emamjomeh
6.  Reza H.Sajedi
7.  Javad Zahiri
  Status:   Published
  Journal: Heliyon
  No.:  7
  Vol.:  4
  Year:  2018
  Pages:   https://doi.org/10.1016/j.heliyon.2018.e00705
  Supported by:  IPM
Various cold-adapted organisms produce antifreeze proteins (AFPs), which prevent the freezing of cell fluids by inhibiting the growth of ice crystals. AFPs are currently being recognized in various organisms, living in extremely low temperatures. AFPs have several important applications in increasing freeze tolerance of plants, maintaining the tissue in frozen conditions and producing cold-hardy plants by applying transgenic technology. Substantial differences in the sequence and structure of the AFPs, pose a challenge for researchers to identify these proteins. In this paper, we proposed a novel method to identify AFPs, using supportive vector machine (SVM) by incorporating 4 types of features. Results of the two used benchmark datasets, revealed the strength of the proposed method in AFP prediction. According to the results of an independent test setup, our method outperformed the current state-of-the-art methods. In addition, the comparison results of the discrimination power of different feature types revealed that physicochemical descriptors are the most contributing features in AFP detection. This method has been implemented as a stand-alone tool, named afpCOOL, for various operating systems to predict AFPs with a user friendly graphical interface.

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