Journal of Proteomics & Bioinformatics
Open Access

Neelima Arora

Publications

• Research Article
  An In Silico Approach to Cluster CAM Kinase Protein Sequences
  Author(s): U.S.N Murty, Amit Kumar Banerjee and Neelima Arora U.S.N Murty, Amit Kumar Banerjee and Neelima Arora
  
  As we are ushering in new age of data driven world, we face an enormous challenge of deriving information from heaps of data available. The amount of data being generated is overwhelming and this calls for exploring novel and effective methods for clustering and classification of such data. CAM kinase family is known to contain many enzymes involved in important physiological processes. In the present study, 13 important physicochemical parameters were calculated for 56 sequences of CAM kinase family in silico. Self organizing Maps (SOM) were employed for the classifying and clustering similar sequences and visualization of high dimensional data spaces as they are known for their capability to maintain the essence of topological relationships between the features. SOM effectively yielded 4 clusters which were distinct from each other and marked by characteristic featu.. View More»
  DOI: 10.4172/jpb.1000066

  Abstract PDF

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