Data Science, Machine Learning, Plant Genetics, Biotechnology, Recombinant DNA Technology
Techniques Neha Mittal Uses:
Machine learning algorithms including supervised and unsupervised learning methods, python, R, R shiny, CLUTO, KEGG
Neha Mittal's Problem Solving Skills:
Python, R, R Shiny, Machine Learning, OOPS, SQL Server
RNA seq Data analysis, Metabolomics, Gene Expression and Gene Transformation Data
Neha Mittal's Problem Solving Experience:
I built up a strategy to identify SNPs (single nucleotide polymorphism) in banana genomic data set and visualize it using python.
My research focus on genomics and metabolomics in soybeans to find the solutions against soybean cyst nematode pathogen. I work on the big data analysis using machine learning, deep learning approaches in python and R. I also have experience to work on molecular cloning functional validation approaches.
I developed a technique which helps in prediction of cis-regulatory modules in human genome in chip-set data.
I developed a method to efficiently analyze the metabolomics data set using R methods
I developed a data visualization app using R shiny to help analyzing and visualizing different complex data sets. This app offers exciting graphs such as heat-maps, clustering, phylogenetic trees along with simple graphs such as box plots, bar graphs etc.
I built a machine learning technique to detect anomalies in wireless sensor networks using ellipsoidal boundary model.