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Auto-Poietic Algorithm for Multiple Sequence
        
        The concept of self-organization is applied to the operators and parameters of genetic algorithm to develop a novel 
Auto-poietic  algorithm  solving  a  biological  problem, Multiple  Sequence  Alignment (MSA).  The  self-organizing  crossover 
operator  of  the  developed  algorithm  undergoes  a  swap  and  shuffle  process  to  alter  the  genes  of  chromosomes  in order  to 
produce  better  combinations.  Unlike Standard  Genetic  Algorithms (SGA),  the  mutation  rate  of  auto-poietic  algorithm  is  not 
fixed. The mutation rate varies cyclically based on the improvement of fitness value in turn, determines the termination point of 
algorithm.  Automated  assignment  of  various  parameter  values  reduces  the  intervention  and  inappropriate  settings  of 
parameters  from  user  without  prior  the  knowledge  of  input.  As  an  advantage,  the  proposed  algorithm  also  circumvents  the 
major issues in standard genetic algorithm, premature  convergence and time  requirements to optimize  the  parameters.  Using 
Benchmark  Alignment  Database (BAliBASE) reference  multiple  sequence  alignments,  the  efficiency  of  the  auto-poietic 
algorithm  is  analyzed.  It  is  evident  that  the  performance  of  auto-poietic  algorithm  is  better  than  SGA  and  produces  better 
alignments compared to other MSA tools.    
            [1] Bao-Juan H., Jian Z., and De-Hong Y., A Novel and Accelerated Genetic Algorithm, WSEAS Transactions on Systems and Control, vol. 3, no. 4, pp. 269-278, 2008.
[2] Carroll H., Beckstead W., O'Connor T., Ebbert M., Clement M., Snell Q., and McClellan D., DNA Reference Alignment Benchmarks Based on Tertiary Structure of Encoded Proteins, Bioinformatics, vol. 23, no. 19, pp. 2648-2649, 2007.
[3] Corpet F., Multiple Sequence Alignment with Hierarchical Clustering, Nucleic Acids Research, vol. 16, no. 22, pp. 10881-10890, 1988.
[4] Djennas S., Bendimerad F., and Meriah S., Genetic Algorithm-Based Synthesis of Three- Dimensional Microstrip Arrays, The International Arab Journal of Information Technology, vol. 2, no. 3, pp. 182-190, 2005.
[5] Edgar R., MUSCLE: Multiple Sequence Alignment with High Accuracy and High Throughput, Nucleic Acids Research, vol. 32, no. 5, pp. 1792-1797, 2004.
[6] Fatumo S., Akinyemi I., and Adebiyi E., Aligning Multiple Sequence with Genetic Algorithm, International Journal of Computer Theory and Engineering, vol. 1, no. 2, pp. 179- 182, 2009.
[7] Gondro C. and Kinghorn B., A simple Genetic Algorithm for Multiple Sequence Alignment, Genetics and Molecular Research, vol. 6, no. 4, pp. 964-982, 2007.
[8] Katoh K., Misawa K., Kuma K., and Miyata T., MAFFT: A Novel Method for Rapid Multiple Sequence Alignment Based on Fast Fourier Transform, Nucleic Acids Research, vol. 30, no. 14, pp. 3059-3066, 2002.
[9] Khayat O., Ebadzadeh M., Shahdoosti H., Rajaei R., and Khajehnasiri I., A Novel Hybrid Algorithm for Creating Self-Organizing Fuzzy Neural Networks, Neurocomputing, vol. 73, no. 1, pp. 517-524, 2009. Auto-Poietic Algorithm for Multiple Sequence Alignment 849
[10] Kubota N., Fukuda T., and Shimojima K., Virus Evolutionary Genetic Algorithm for ASelf- Organizing Manufacturing System, Computers and Industrial Engineering, vol. 30, no. 4, pp. 1015-1026, 1996.
[11] Mansour N., Awad M., and El-Fakih K., Incremental Genetic Algorithm, The International Arab Journal of Information Technology, vol. 3, no. 1, pp. 42-47, 2006.
[12] Morgenstern B., Dress A., and Werner T., Multiple DNA and Protein Sequence Based on Segment-to-Segment Comparison, in Proceedings of the National Academy of Sciences, vol. 93, no. 22, pp. 12098-12103, 1996.
[13] Nizam A., Shanmugham B., and Subburaya K., Self-Organizing Genetic Algorithm for Multiple Sequence Alignment, Global Journal of Computer Science and Technology, vol. 11, no. 7, pp. 7-14, 2011.
[14] Nizam A. and Shanmugham B., Self-Organizing Multi-mutation Algorithm for Multiple Sequence Alignment, in Proceedings of 15th International Conference on Advanced Computing Technologies, Rajampet, 2013.
[15] Notredame C., Higgins D., and Heringa J., T- Coffee: A Novel Method for Fast and Accurate Multiple Sequence Alignment, Journal of Molecular Biology, vol. 302, no. 1, pp. 205-217, 2000.
[16] Notredame C., Recent Progresses in Multiple Sequence Alignment: A Survey, Pharmacogenomics, vol. 3, no. 1, pp. 131-144, 2002.
[17] Seeley T., When Is Self-Organization Used in Biological Systems?, The Biological Bulletin, vol. 202, no. 3, pp. 314-318, 2002.
[18] Thompson J., Higgins D., and Gibson T., CLUSTAL W: Improving the Sensitivity of Progressive Multiple Sequence Alignment through Sequence Weighting Position Specific Gap Penalties and Weight Matrix Choice, Nucleic Acids Research, vol. 22, no. 22, pp. 4673- 4680, 1994.
[19] Tin os R. and Yang S., Self-Organizing Random Immigrants Genetic Algorithm for Dynamic Optimization Problems, Genetic Programming and Evolvable Machines, vol. 8, no. 3, pp. 255- 286, 2007.
[20] Wu S., Lee M., Lee Y., and Gatton T., Multiple Sequence Alignment Using GA and NN, International Journal of Signal Processing, Image Processing and Pattern Recognition, vol. 1, no. 1, pp. 21-30, 2008.
[21] Zhang J., Zhuang J., Du H., and Wang S., Self- Organizing Genetic Algorithm Based Tuning of PID Controllers, Information Sciences, vol. 179, no. 7, pp. 1007-1018, 2009. Amouda Venkatesan is currently working as an Assistant Professor in the Centre for Excellence in Bioinformatics, Pondicherry University, India. She received the master degree in Software System from BITS Pilani and Doctorate degree in Computer Science and Engineering from Pondicherry University. She has more than 12 years of teaching experience. Her principle area of interests is Genetic algorithm and published more than 25 research publications. Buvaneswari Shanmugham is pursuing Ph.D. Bioinformatics in the Centre for Excellence in Bioinformatics, Pondicherry University, India. She received her M.Sc. degree in Bioinformatics in the year 2010. She has published six research papers in International journals and conferences. Her area of research includes Genetic algorithm and Comparative genomics.
