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IPM
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“School of Biological Sciences”

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Paper   IPM / Biological Sciences / 13184
School of Biological Sciences
  Title:   Prediction Of Protein Submitochondria Locations Based On Data Fusion Of Various Features Of Sequences
  Author(s): 
1.  P. Zakeri.
2.  B. Moshiri.
3.  M. Sadeghi.
  Status:   Published
  Journal: Journal of Theoretical Biology
  No.:  1
  Vol.:  269
  Year:  2011
  Pages:   208-216
  Supported by:  IPM
  Abstract:
In this study, the predictors are developed for protein submitochondria locations based on various features of sequences. Information about the submitochondria location for a mitochondria protein can provide much better understanding about its function. We use ten representative models of protein samples such as pseudo amino acid composition, dipeptide composition, functional domain composition, the combining discrete model based on prediction of solvent accessibility and secondary structure elements, the discrete model of pairwise sequence similarity, etc. We construct a predictor based on support vector machines (SVMs) for each representative model. The overall prediction accuracy by the leave-one-out cross validation test obtained by the predictor which is based on the discrete model of pairwise sequence similarity is 1more info : http://www.sciencedirect.com/science/article/pii/S0022519310005606

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