Analysis of cancer gene attributes using electrical sensor.

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.