Mathanakumara E.

I am a highly motivated individual with extensive experience in multiple programming languages (Python, Bash, Perl) and a deep understanding of bulk RNA-seq ( Oxford Nanopore Technology, Illumina, PacBio), single-cell RNA-seq and spatial transcriptomics. Throughout my academic and professional journey, I have developed a robust knowledge base in utilizing various genomic and transcriptomic aligners, as well as downstream bioinformatics tools for both identification and quantification purposes, differential expression analysis algorithms and generating visually impactful graphs such as ggplot2, Matplotlib, Seaborn, and Plotly. Moreover, I have designed a novel pipeline to outperform conventional methods in identifying circRNAs and is proven to be more effective through benchmarking studies using simulated datasets. I have even modified existing algorithms to enable my team to analyze current data that fits our objectives. For example, I have modified a python algorithm that was initially designed in finding relationships between circRNAs and miRNAs to enable it to also identify relationship between miRNA and mRNA. From this results, we were able to form a competing endogenous RNA network, linking circRNAs to mRNA. In addition to my current expertise, I have a strong and ongoing interest in learning all other forms of sequence analysis such MNase-seq, ATAC-seq and so on. For example, I have independently learned to analyze both single-cell and spatial transcripts through online materials and Youtube. This demonstrates my unquenchable thirst to learn and my enthusiasm for expanding my skill set beyond the current level. Furthermore, I have hands-on experience with SLURM Linux batch HPC systems, a knowledge crucial for this position. My ability to submit, manage and troubleshoot RNA-seq analysis jobs on HPC systems has been integral to my success in previous roles. I have also shared some of my scripts in my personal GitHub account (Mathan98). Beyond my technical skills, I bring strong interpersonal abilities to the table, including independence, problem-solving, multi-tasking, quick learning, and adaptability. For example, despite starting with no prior experience in bioinformatics, I completed my Master’s degree in just 3 years, a testament to my ability to rapidly acquire new skills and tackle research challenges effectively. Moreover, throughout my tenure as a Graduate Research Assistant (GRA), I have been tasked with sample prepping, troubleshooting problems, mentoring students and document relevant research publications. All these has honed my ability to communicate complex biological and coding concepts in a clear and accessible manner. I am confident that my background and skills align well with the Bioinformatics project you bring forward. I would welcome the opportunity to discuss more on how my experiences and interests align with the needs of your team. Hope to hear from you soon.