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Papers by Nivit Gill

The epilepsy is serious neurological disorder which disturb the common activities of person with... more The epilepsy is serious neurological disorder which disturb the common activities of person with recurret seizures. The electroencephalogram (EEG) signal is used to analyze for the detection of epilepsy seizure. This paper presents new spike based feature as it is one of main characteristics of epilepsy prone EEG. The IMFs (Intrinsic Mode Decomposition) of the EEG is calculated by employing EMD (Empirical Mode Decomposition) and first five IMFs are used in proposed study. Since the presence of spikes increases the amplitude of signal, maximum value of each IMF is used as feature to train the classifier. The classification of EEG signal into seizure or no-seizure is done by using ANN (Artificial neural networks). The results of the each IMF is recorded individually and concluded the third IMF shows the best presence of spikes. The results of proposed method is also compare with other existing techniques for the validation.

International Journal of Computer Applications, 2013

International Journal of Computer Applications, 2012

Journal of Computational Biology, 2014

Bioinformatics aids in the understanding of the biological processes of living beings and the gen... more Bioinformatics aids in the understanding of the biological processes of living beings and the genetic architecture of human diseases. The discovery of disease-related genes improves the diagnosis and therapy design for the disease. To save the cost and time involved in the experimental verification of the candidate genes, computational methods are employed for ranking the genes according to their likelihood of being associated with the disease. Only top-ranked genes are then verified experimentally. A variety of methods have been conceived by the researchers for the prioritization of the disease candidate genes, which differ in the data source being used or the scoring function used for ranking the genes. A review of various aspects of computational disease gene prioritization and its research issues is presented in this article. The aspects covered are gene prioritization process, data sources used, types of prioritization methods, and performance assessment methods. This article provides a brief overview and acts as a quick guide for disease gene prioritization.

IJCSET BOARD MEMBERS, Jan 1, 2011

International Journal of Computer …, Jan 1, 2011

The epilepsy is serious neurological disorder which disturb the common activities of person with... more The epilepsy is serious neurological disorder which disturb the common activities of person with recurret seizures. The electroencephalogram (EEG) signal is used to analyze for the detection of epilepsy seizure. This paper presents new spike based feature as it is one of main characteristics of epilepsy prone EEG. The IMFs (Intrinsic Mode Decomposition) of the EEG is calculated by employing EMD (Empirical Mode Decomposition) and first five IMFs are used in proposed study. Since the presence of spikes increases the amplitude of signal, maximum value of each IMF is used as feature to train the classifier. The classification of EEG signal into seizure or no-seizure is done by using ANN (Artificial neural networks). The results of the each IMF is recorded individually and concluded the third IMF shows the best presence of spikes. The results of proposed method is also compare with other existing techniques for the validation.

International Journal of Computer Applications, 2013

International Journal of Computer Applications, 2012

Journal of Computational Biology, 2014

Bioinformatics aids in the understanding of the biological processes of living beings and the gen... more Bioinformatics aids in the understanding of the biological processes of living beings and the genetic architecture of human diseases. The discovery of disease-related genes improves the diagnosis and therapy design for the disease. To save the cost and time involved in the experimental verification of the candidate genes, computational methods are employed for ranking the genes according to their likelihood of being associated with the disease. Only top-ranked genes are then verified experimentally. A variety of methods have been conceived by the researchers for the prioritization of the disease candidate genes, which differ in the data source being used or the scoring function used for ranking the genes. A review of various aspects of computational disease gene prioritization and its research issues is presented in this article. The aspects covered are gene prioritization process, data sources used, types of prioritization methods, and performance assessment methods. This article provides a brief overview and acts as a quick guide for disease gene prioritization.

IJCSET BOARD MEMBERS, Jan 1, 2011

International Journal of Computer …, Jan 1, 2011

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