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Analysis of cancer gene attributes using electrical sensor T
University of Engineering and Management, Kolkata 700156, India
Prediction of cancer gene attributes by their primary structure (long amino acid sequence) is instrumental in large-scale genomics projects, especially in the field of genomics. Various methods are proposed to predict gene characteristics from its primary structure, but accurate prediction of it is still very challenging task. Here we introduce an electrical network based sensor or detector to discriminate cancer and non-cancer cells based on two features i.e. amino acid sequence length, and hydrophilic/hydrophobic property. The electrical circuit consists of resistors, capacitors and inductors, is used for modeling individual amino acid and cascaded to form gene system. Corresponding electrical responses are judged using Bode and Nyquist analyzers and achieve 89.55% accuracy with 87.06% True Positive rate and 95.42% True Negative rate, demonstrate that proposed electrical sensor model is very promising for predicting the cancer gene attributes as well as non-cancer gene in the field of large-scale genomics study.
In recent years, complex network modeling is gaining importance in nanobioscience and genomic research. Several researchers proposed diﬀerent type of complex network approaches to model deoxyr-ibonucleic acid (DNA)/ribonucleic acid (RNA), amino acid and protein structure. Resistor-capacitor ladder network is used to develop model for DNA/RNA strings at nucleotide level (Marshall, 2010a). Passive analog electrical circuits are designed for protein structure (Sampath, 2006). The secondary structure and the secondary structure linkages are modeled using resistor, capacitor and inductor (Marshall, 2010b). Electrical network models are also developed to study the structural and electrical properties of DNA, protein, gene etc. (Hodzic and Newcomb, 2007; Alfinito et al., 2008; Roy et al., 2014; Roy and Barman, 2014).