I'm Arun Seetharam, a Lead Bioinformatics Scientist at Purdue University’s Rosen Center for Advanced Computing (RCAC).

I provide bioinformatics support to researchers, specializing in genome assembly, annotation, and creating efficient, reproducible workflows on high-performance computing (HPC) platforms. I lead bioinformatics projects, mentor junior scientists, and manage complex data analysis needs for academic and research clients.

I bring over 10 years of bioinformatics expertise, with hands-on experience in developing computational tools and workflows. If you need guidance on complex genome analyses, project management in bioinformatics, or assistance with optimizing workflows in HPC, I am here to help. My experience spans a wide range of organisms, and I’ve developed robust solutions for both large-scale collaborative projects and individual research needs.

I wish I’d known the importance of efficient workflow management systems, like Nextflow and Snakemake, sooner. These tools greatly enhance reproducibility and scalability, essential for bioinformatics on HPC.

I'm focused on expanding my skills in gene prediction and annotation, particularly in understanding complex polyploid genomes. It’s an area of bioinformatics that is challenging and might be transformative for crop improvement and evolutionary biology studies, as these genomes often hold insights into adaptive traits and species resilience.

Once I complete the analyses for a project, I make sure to document everything thoroughly. This way, the workflow is reproducible and easy for others or myself in the future—to rerun without the hassle of figuring out the setup again.

I believe my collaborative approach has been a key factor. Bioinformatics requires both technical depth and the ability to work across disciplines, and being able to communicate complex technical information to diverse teams has allowed me to succeed.

My first job was as a Technical Assistant at the University of Agricultural Sciences in Dharwar, India, where I worked on creating genetic linkage mapping and QTL analysis in sorghum (stay-green trait). It provided foundational research experience and insights into genomics.

Maybe, some aspects of my early research assistant roles, where administrative hurdles limited research progress, were challenging. I learned that strategic project management and clear communication are essential for successful project execution.

My current role is my favorite because it allows me to combine technical problem-solving with collaborative research. I have the opportunity to directly impact scientific discoveries through bioinformatics and work with a vibrant research community.

Working at core facilities, I sometimes focused too heavily on technical perfection rather than timely project completion. I learned that balancing accuracy with efficiency is key in research and that delivering results within deadlines can be more impactful.

I have a strong background in both biology and computing, and bioinformatics was a natural intersection. My graduate studies in phylogenomics sparked my interest in using computational tools to solve biological questions, leading me to specialize in genome informatics.

I’m excited about building reusable, efficient workflows for genomics analyses, gene prediction optimization and exploring structural variations in cancer genomes. I’m also excited to support collaborative research, which brings in diverse perspectives and challenges.

The collaborative culture and focus on innovation have been impressive. RCAC fosters an environment where there's a strong commitment to pushing the noundaries of computational research support.

I'm proud of developing/contributing to the Bioinformatics Workbook and several open-source tools that have become valuable resources for the bioinformatics community, helping others streamline and enhance their own research processess.

Many think bioinformatics is purely technical; however, a large part of my role involves stratgic project planning, collaboration, and translating complex data analyses into actionable insights for research teams.

I joined Purdue and RCAC as a Lead Bioinformatics Scientist in July 2024.

I hold a Ph.D. in Biology from Indiana State University. I have >40 publications in peer-reviewed journals and am actively engaged in several professional organizations, including the Research Data Alliance, MaizeGDB, and the Society for Molecular Biology and Evolution.

In my spare time, I enjoy perfecting my homemade pizza and bagel recipes. I've even shared these recipes on GitHub (pizza, bagel). My other hobbies include running and gardening (during summer).

I decided to become a mentor for the REU program because bioinformatics sits at a fascinating intersection of biology, computer science, and data analytics. Mentoring in this program allows me to guide students as they navigate these cross-disciplinary fields, helping them understand how to combine diverse skills to solve real-world research problems. The collaborative nature of bioinformatics means we often work with experts across genomics, software engineering, and HPC, and I find it incredibly rewarding to introduce students to this collaborative environment, showing them how teamwork and cross-disciplinary knowledge can drive innovation and deepen scientific insights.

1. What do you hope the REU gets out of the program?

   I hope REU students come away with a strong understanding of how cross-disciplinary collaboration can drive scientific progress. Bioinformatics is uniquely positioned at the intersection of biology, data science, and computing, so learning to integrate these skills is invaluable. I want students to see firsthand how bringing together diverse expertise can lead to innovative solutions in genomics.

2. How can this help them in their college career?

   The program equips students with advanced computational skills that will make complex analyses manageable and reproducible. These skills are invaluable in academia, helping students tackle more ambitious projects, and giving them an edge in research-oriented coursework.

3. How can this help them in their professional career?

   Knowledge of HPC and bioinformatics workflows is in high demand across biotech, genomics, and data-intensive fields. The experience students gain will make them competitive candidates for roles requiring data-driven insights and efficient problem-solving capabilities.

As a mentor, I gain the rewarding experience of fostering cross-disciplinary growth in early-career researchers. Mentoring allows me to share my own experience working at the intersection of biology and computing while also learning from the fresh perspectives students bring. This exchange of ideas strengthens my own collaborative skills and reinforces the importance of interdisciplinary thinking, which is vital in advancing bioinformatics and genomics research.

The REU project is titled "Bioinformatics Workflow Templates for Genomics Analyses." Students will create user-friendly templates for common genomics analyses, such as RNA-seq, variant calling, and genome assembly, with pre-configured scripts, SLURM job files, and optimal resource settings tailored for HPC. This project is aimed at researchers comfortable with the command line but not necessarily with workflow managers, focusing on usability, resource efficiency, and reproducibility.

I’ve never been an intern during my undergraduate studies, as there wasn’t a similar program available in my country at the time. This experience gives me a unique perspective, as I recognize the immense value of hands-on research opportunities like the REU program, which can be pivotal for students in shaping their careers.