Thursday 28th of March 2024
 

Data optimization from a multiple species network using modified SFLA(Shuffled Frog Leaping Algorithm)


N. Kannaiya Raja, N. Kannaiya Raja, K. Arulanandam, K. Arulanandam, and S. K. Sugunedham

In this work we present a novel approach that uses interspecies sequences homology to connect the networks of multi species and possible more species and possible more species together with gene ontology dependencies in order to improve protein classification for research work. Proteins are involved in many for all biological process such energy metabolism, signal transduction and translation initiation. Even though for a large portion of proteins and their biological function are unknown or incomplete, therefore constructing efficient and reliable models for predicting the protein function has to be used in research work. Our method readily extends to multi species food and produce the improvements similar to them multi species. In the presence of multi interacting networks are using data mining for integration of a data from various sources and contributing increased accuracy of the function prediction of the multiple species for research work. We further enhance our model to account for the gene ontology dependencies by linking multiple related ontology categories such as, we have selected the food items from various countries such as from America the famous food items of yoghurt and Australia food items of oats and Indian food items of soya bean. The data sets are highly desirable for this use from various countries using logical networks from center for bioinformatics research institute (Chennai) and stored in the mining.SFLA aims to set a generic paradism of the efficient mining that acquire the data set of proteins for these food items and promotes predictions of protein functions with gene ontology for research work.

Keywords: Biology and genetics, machine learning, bioinformatics (genome or protein) databases.

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ABOUT THE AUTHORS

N. Kannaiya Raja
computer science engg dept

N. Kannaiya Raja
Mr.N.Kannaiya Raja received degree MCA from Alagappa University and ME from Anna University Chennai in 2007 joined assistant professor in various engineering colleges in Tamil Nadu affiliated to Anna University and has eight years teaching experience. His research work in deep packet inspection. He has been session chair in major conference and workshops in computer vision on algorithm, network, mobile communication, image processing papers and pattern recognition. His current primary areas of research are packet inspection and network. He is interested to conduct guest lecturer in various engineering in Tamil Nadu.

K. Arulanandam
computer science engineering dept.

K. Arulanandam
2Dr.Mr..KArulanandam received PhD doctorate degree in 2010 from Vinayaka Missions University. He has twelve years teaching experience in various engineering colleges in Tamil Nadu which are affiliated to Anna University and his research experience network, mobile communication tworks, image processing papers and algorithm papers. Currently working in Ganadipathy Tulasi’s Jain Engineering College Vellore




S. K. Sugunedham
S.K.Sugunedham received degree B.Tech Computer Science Engineering from Pondicherry University Puducherry in 2010. Now pursuing ME Computer Science and Engineering in Arulmigu Meenakshi Amman College of Engineering Kanchipuram affiliated to Anna University Chennai.


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