Areas Neha Mittal is Knowledgeable in:
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.