-Conducted a comprehensive analysis of single-cell genomics data derived from Sarcoma, utilizing advanced methodologies such as scRNA-seq, snRNA-seq, and scATAC-seq-Analyzed Single Cell Multi-omics data using Cell Ranger ARC software-Annotated Cell-types for single cell RNA-seq data using Scanpy and Seurat packages-Evaluated the response of Sarcoma to immunotherapeutic approaches (CAR T-cell therapy)-The report is available upon request and can be confirmed by Dr. Sorana Morrissy

My main duties include:- Annotated Cell-types for single cell RNA-seq data using Scanpy Python package and SeuratR package- Initiated and led the integration of ligand-receptor interaction analysis using CellphoneDB,CellChat, and Nichenet for the purpose of drug discovery- Computed the pathway activity score based on the expression of the genes associated with apathway to identify major signalling pathways for each cancer type- Utilized single-cell and immune sequencing to forecast treatment outcomes and patientresponses- Identified cancer cells at the single-cell level using InferCNV- Identified cancer-specific biomarkers by analyzing differentially expressed genes, transcripts,and proteins between cancerous and normal cells- Analyses were conducted on multi-omics and immunomics data from squamous cell lungcarcinoma, til therapy for lung carcinoma, leptomeningeal metastases, stomach (gastric)cancer and MSK SPECTRUM project

Defended Thesis titled: "Detectability of Non-Equilibrium Molecular Evolution Caused byFitness Shift and Drift"- Developed a mechanistic modeling framework of codon fitness shift and drift- Characterised the consequence of non-equilibrium molecular evolution in terms of dN/dSand expected frequency of each amino acid- Evaluated the performance of existing branch-site methods to detect fitness shift fromepisodic changes in population size- The report is available upon request and can be confirmed by Dr. Jason de KoningTeaching Assistant- Interdisciplinary approaches to research (bioinformatics section), Dr. Jason de Koning-

Implemented a machine learning algorithm for detecting trisomy in the fetus for Non-invasivePrenatal Testing (NIPT) data- Optimized the use of transcription factors (TFs) in the context of cellular reprogrammingusing gene expression and structural controllability (controllability of complex systems)-