Sivasharmini Ganeshamoorthy

Computational Biology

• Inferring Gene Regulatory Network through machine learning approaches.

Research Project: “Computational Biology and Gene Network Inference: Study that effects of diurnal asymmetric warming on plant defense and growth”

To sustain and improve plant productivity in this biotic and abiotic situation, it is essential to produce stress-resistance crops. The aim of this project is to use mathematical and computational models to develop a gene regulatory network to identify which genes or transcripts have significant expression variation across different experimental conditions of interest.

Research Project: “Detecting Alzheimer's disease through EEG Signals using non-linear feature extraction”

Alzheimer’s disease (AD) which is a common type of Dementia is one of the neurodegenerative disorders which is currently a life-threatening disease among elderly people.Electroencephalography (EEG) is an economical and non-invasive neuro imaging tool that includes special characteristics such as non-linear, non-stationery and complex to diagnose AD. The main aim of this research is to extract information from EEG using Information theoretical techniques to diagnose Alzheimer’s disease. Among number of feature extraction methods in EEG, information length which is a novel approach for neuroscience has been adopted for this study. Information length is considered to be an effective method to capture the spatial and temporal dynamics in the dataset. The extracted features are used to classify AD through Support Vector Machine (SVM) classifier.