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A Comparative Study on Filtering Protein Secondary Structure Prediction
May-June 2012 (vol. 9 no. 3)
pp. 731-739
ASCII Text
x 
 
G. Christodoulou, V. J. Promponas, M. Agathocleous, P. Kountouris, S. Hadjicostas, V. Vassiliades, C. Christodoulou, "A Comparative Study on Filtering Protein Secondary Structure Prediction," IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 9, no. 3, pp. 731-739, May-June, 2012.
 
 
BibTex
x
 
@article{ 10.1109/TCBB.2012.22,
author = {G. Christodoulou and V. J. Promponas and M. Agathocleous and P. Kountouris and S. Hadjicostas and V. Vassiliades and C. Christodoulou},
title = {A Comparative Study on Filtering Protein Secondary Structure Prediction},
journal ={IEEE/ACM Transactions on Computational Biology and Bioinformatics},
volume = {9},
number = {3},
issn = {1545-5963},
year = {2012},
pages = {731-739},
doi = {http://doi.ieeecomputersociety.org/10.1109/TCBB.2012.22},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE/ACM Transactions on Computational Biology and Bioinformatics
TI - A Comparative Study on Filtering Protein Secondary Structure Prediction
IS - 3
SN - 1545-5963
SP731
EP739
EPD - 731-739
A1 - G. Christodoulou,
A1 - V. J. Promponas,
A1 - M. Agathocleous,
A1 - P. Kountouris,
A1 - S. Hadjicostas,
A1 - V. Vassiliades,
A1 - C. Christodoulou,
PY - 2012
KW - proteins
KW - bioinformatics
KW - filtering theory
KW - learning (artificial intelligence)
KW - molecular biophysics
KW - molecular configurations
KW - empirical rule
KW - protein secondary structure prediction filtering
KW - machine learning technique
KW - Accuracy
KW - Proteins
KW - Filtering
KW - Machine learning algorithms
KW - Logistics
KW - Training
KW - Machine learning
KW - bidirectional recurrent neural networks.
KW - Protein secondary structure prediction
KW - filtering
KW - machine learning
KW - structural bioinformatics
VL - 9
JA - IEEE/ACM Transactions on Computational Biology and Bioinformatics
ER -
 
G. Christodoulou, Dept. of Comput. Sci., Univ. of Cyprus, Nicosia, Cyprus
V. J. Promponas, Dept. of Biol. Sci., Univ. of Cyprus, Nicosia, Cyprus
M. Agathocleous, Dept. of Comput. Sci., Univ. of Cyprus, Nicosia, Cyprus
P. Kountouris, Dept. of Comput. Sci., Univ. of Cyprus, Nicosia, Cyprus
S. Hadjicostas, Dept. of Comput. Sci., Univ. of Cyprus, Nicosia, Cyprus
V. Vassiliades, Dept. of Comput. Sci., Univ. of Cyprus, Nicosia, Cyprus
C. Christodoulou, Dept. of Comput. Sci., Univ. of Cyprus, Nicosia, Cyprus
Filtering of Protein Secondary Structure Prediction (PSSP) aims to provide physicochemically realistic results, while it usually improves the predictive performance. We performed a comparative study on this challenging problem, utilizing both machine learning techniques and empirical rules and we found that combinations of the two lead to the highest improvement.

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Index Terms:
proteins,bioinformatics,filtering theory,learning (artificial intelligence),molecular biophysics,molecular configurations,empirical rule,protein secondary structure prediction filtering,machine learning technique,Accuracy,Proteins,Filtering,Machine learning algorithms,Logistics,Training,Machine learning,bidirectional recurrent neural networks.,Protein secondary structure prediction,filtering,machine learning,structural bioinformatics
Citation:
G. Christodoulou, V. J. Promponas, M. Agathocleous, P. Kountouris, S. Hadjicostas, V. Vassiliades, C. Christodoulou, "A Comparative Study on Filtering Protein Secondary Structure Prediction," IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 9, no. 3, pp. 731-739, May-June 2012, doi:10.1109/TCBB.2012.22
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