Application of Genetic Programming (GP) Formalism for Building Disease Predictive Models from Protein-Protein Interactions (PPI) Data
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @Article{Vyas:2016:TCBB,
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author = "Renu Vyas and Sanket Bapat and Purva Goel and
M. Karthikeyan and S. S. Tambe and B. D. Kulkarni",
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journal = "IEEE/ACM Transactions on Computational Biology and
Bioinformatics",
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title = "Application of Genetic Programming (GP) Formalism for
Building Disease Predictive Models from Protein-Protein
Interactions (PPI) Data",
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year = "2016",
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abstract = "Protein-protein interactions (PPIs) play a vital role
in the biological processes involved in the cell
functions and disease pathways. The experimental
methods known to predict PPIs require tremendous
efforts and the results are often hindered by the
presence of a large number of false positives. Herein,
we demonstrate the use of a new Genetic Programming
(GP) based Symbolic Regression (SR) approach for
predicting PPIs related to a disease. In a case study,
a dataset consisting of one hundred and thirty five PPI
complexes related to cancer was used to construct a
generic PPI predicting model with good PPI prediction
accuracy and generalisation ability. A high correlation
coefficient(CC) of 0.893, low root mean square error
(RMSE) and mean absolute percentage error (MAPE) values
of 478.221 and 0.239, respectively were achieved for
both the training and test set outputs. To validate the
discriminatory nature of the model, it was applied on a
dataset of diabetes complexes where it yielded
significantly low CC values. Thus, the GP model
developed here serves a dual purpose: (a)a predictor of
the binding energy of cancer related PPI complexes, and
(b)a classifier for discriminating PPI complexes
related to cancer from those of other diseases.",
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keywords = "genetic algorithms, genetic programming",
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DOI = "doi:10.1109/TCBB.2016.2621042",
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ISSN = "1545-5963",
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notes = "Also known as \cite{7707365}",
- }
Genetic Programming entries for
Renu Vyas
Sanket Bapat
Purva Goel
M Karthikeyan
Sanjeev S Tambe
Bhaskar D Kulkarni
Citations