KETAKI GHATOLE
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Hi there!
I am driven by a passion for using computational methods to unravel the intricacies of complex biological systems.
My interests lie in developing bioinformatics pipelines and applying machine learning techniques to omics and biomedical imaging data, enhancing our comprehension of these systems. My unique background, bridging life sciences and consulting, enriches my approach, allowing for innovative problem-solving strategies.
Holding a Master's degree in Computational Biology from Carnegie Mellon University, and currently working as a Data Analyst at Creyon Bio, I am committed to using my skills to drive meaningful innovations in the field.
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Feel free to reach out for collaborations, ideas or just to chat
EXPERIENCE
EXPERIENCE
Data Analyst
Building scalable bioinformatics pipeline and ML models to extracting meaningful insights
Computational biology intern
Provided analytical support including DE analysis, WGBS, Spatial transcriptomic alnalyses to researchers
Computational Science intern
Analyzed e-CLIP data to develop a web-based application to predict and visualize potential RNA binding motifs​
Junior Analyst
Automated the data collection to perform competitive landscape for emerging therapeutic agents in Oncology
PROJECTS
MACHINE LEARNING
Lung Cancer Classifier
Multi-omic analyses for Lung Cancer classification using Autoencoders, SVM, and Random Forest
Malaria detector
Detected malaria parasites in blood smear images using transfer learning with the ResNet50 architecture
Glioma classifier
Glioma Classification using four supervised multiclass classifiers based on gene expression data
BIOINFORMATICS
Variant Calling
Pipeline to identify SNPs and indels in paired-end sequencing data using GATK
RBP Peak Finder
Developed a pipeline to process e-CLIP data from ENCORE and obtain the peaks
Codon Usage Bias
Evaluated the amino acid preferences and codon usage patterns for a given sequence