A Novel Local And Global Similarity Based Feature...

A Novel Local and Global Similarity based Feature Extraction Approach for Protein Classification Abstract—In this article, a novel approach is proposed based on local and global similarity for extracting features from protein sequences. The proposed approach extract only 6 features corresponding to each protein sequence. These features are computed by globally considering the probabilities of occurrences of the amino acids in different position of the sequences which locally belongs to the six exchange groups [1]. Then, these features are used as an inputs for Neural Network learning algorithm named as Boolean-Like Training Algorithm (BLTA) [2]. The BLTA classifier is used to classify the protein sequences obtained from the Protein Information Resource (PIR) maintained by the National Biomedical Research Foundation (NBREF-PIR) [3]. To investigate the efficacy of proposed feature extraction approach, the experimentation is performed on two superfamilies, namely Ras and Globin. Across tenfold cross validation, the highest Classification Accuracy and Computational Time achieved by proposed approach is 94.323.52 and 6.54(s) respectively in comparison to the Classification Accuracies achieved by other approaches [4], [5] and [6] are 85.420.55, 67.518.38, 51.410.27 with Computational Time 7.11(s), 10.13(s), 63.98(s) respectively. The experimental results demonstrate that the proposed approach extract the minimum relevant features for each protein sequence. Therefore, itShow MoreRelatedData Mining16277 Words   |  66 Pagessequential data, we mean data that is ordered with respect to some index. For example, time series constitute a popular class of sequential data, where records are indexed by time. Other examples of sequential data could be text, gene sequences, protein sequences, lists of moves in a chess game etc. Here, although there is no notion of time as such, the ordering among the records is very important and is central to the data description/modelling. Time series analysis has quite a long history. TechniquesRead MoreMerck Case18783 Words   |  76 Pages203-432-9395 (Fax: 5963) e-mail: william.rapp@yale.edu Revised December 1998 Table of Contents 1. Introduction: Objective of this Study 2. The Pharmaceutical Industry in a Global Context 3. Product RD and Clinical Trials 4. Manufacturing and Process RD 5. Technological Factors Structure-Based Drug (Rational Drug) Design Structure-Based Drug (Rational Drug) Design 6. Merck 7. Managerial Decision Making 8. Decision Making on IT projects 9. Joint Ventures 10. Information Technology and Organization Read MoreOne Significant Change That Has Occurred in the World Between 1900 and 2005. Explain the Impact This Change Has Made on Our Lives and Why It Is an Important Change.163893 Words   |  656 Pagespoints both before the year 2000 (the collapse of the Soviet Union, the reunification of Germany, the surge of globalization from the mid-1990s) and afterward (9/11, or the global recession of 2008) when one could quite plausibly argue that a new era had begun. A compelling case can be made for viewing the decades of the global scramble for colonies after 1870 as a predictable culmination of the long nineteenth century, which was ushered in by the industrial and political revolutions of the late