PhD Researcher – Deep Neural Network Algorithm Development for Plant Glycosyltransferase Prediction
As part of my PhD work, I developed deep neural network algorithms for the prediction and classification of plant glycosyltransferases. This involved analyzing large-scale genomic and proteomic data sets using deep learning techniques. I conducted labeling and classification tasks on plant genomic sequences to train and validate the predictive models. • Conducted annotation and classification of plant genomic and proteomic sequences for machine learning inputs. • Managed feature engineering and curation of datasets to optimize neural network model performance. • Utilized programming languages such as Python and R for data preprocessing and labeling pipelines. • Engaged in regular evaluation and refinement of labeled datasets and model outputs.