The Indian-American Scientists Revolutionizing Bioinformatics and Genomics
Across the United States, a vibrant community of Indian-origin scientists is helping transform how we understand life itself. They are the architects and engineers of bioinformatics and genomics—fields that mine the vast digital universe of genetic data for insights that can improve human health, combat disease, and feed the planet.
In a California lab, Dr. Venkatesan Sundaresan studies the intricate genetic blueprint of rice, searching for keys to global food security. Meanwhile, in New York, Dr. Shruti Naik deciphers the complex conversation between immune cells and skin tissue, seeking breakthroughs for inflammatory diseases. What connects these scientists—besides their groundbreaking work—is their shared heritage and their position at the forefront of a scientific revolution: the fusion of biology with computational science.
Developing methods and software for understanding biological data
Studying the structure, function, evolution, and mapping of genomes
These researchers stand at the intersection of tradition and innovation, building upon a storied legacy of Indian scientific excellence while pioneering new frontiers in data-driven biology 1 .
Indian-born scientists have a long history of groundbreaking contributions to Western science, with luminaries like Har Gobind Khorana (who shared the 1968 Nobel Prize for deciphering the genetic code) setting the stage for today's researchers. The current generation builds upon this foundation, navigating complex biological questions with sophisticated computational tools.
| Scientist | Institutional Affiliation | Key Contributions | Honors |
|---|---|---|---|
| Venkatesan Sundaresan | UC Davis | Plant reproduction and synthetic apomixis for crop improvement | Wolf Prize in Agriculture (2024), US National Academy of Sciences 1 3 |
| Shruti Naik | Icahn School of Medicine at Mount Sinai | Immunology, stem cell biology, and tissue inflammation | L'Oréal-UNESCO Award, NIH Director's New Innovator Award 1 3 |
| Inder Verma | Salk Institute (emeritus) | Cancer biology and viral vectors for gene therapy | Former editor-in-chief of PNAS 1 |
| Utpal Banerjee | UCLA | Genetics, developmental biology, and stem cell research | NIH Director's Pioneer Award, US National Academy of Sciences 1 |
| Anshul Kundaje | Stanford University | Computational genomics and machine learning | Organizer of Genome Informatics conference 9 |
Interdisciplinary Training
International Collaboration
Mentorship & Leadership
The turning point came with the completion of the Human Genome Project in 2003, which provided the first complete sequence of human DNA. This milestone marked biology's transformation into a data-intensive science—a field where the primary challenge shifted from gathering information to making sense of overwhelming volumes of it.
"The shift from ASM NGS to ASM BIG mirrors the rapid transformation of microbial sciences, where the challenge is no longer just sequencing data—it is making sense of it, managing it and applying it to solve real-world problems," noted organizers of the newly launched ASM Bioinformatics, Genomics and Big Data Conference 2 .
While the project is based in India, its implications ripple across global science, with many Indian-origen researchers in the US contributing to similar large-scale genomic initiatives. The project exemplifies the type of research that this community is advancing worldwide.
Researchers gathered blood samples from 10,074 healthy and unrelated Indians representing 85 diverse populations across the country, including both tribal and non-tribal groups 7 .
Using advanced sequencing machines, the team read the complete genetic code of each participant, generating strings of A's, T's, C's, and G's that make up their individual genomes.
Bioinformatics specialists compared each sequenced genome to a reference human genome, identifying points of difference called "variants."
Computational biologists grouped the genetic variants based on which populations they appeared in, identifying which were common across groups and which were unique to specific communities.
The preliminary findings, published in Nature Genetics in April 2025, revealed 180 million genetic variants—positions in the DNA sequence where the studied individuals differed from one another or from the reference human genome 7 .
Genetic Variants Identified
Populations Represented
Individuals Analyzed
| Category | Finding | Potential Application |
|---|---|---|
| Total variants identified | 180 million | Baseline for Indian population genomics |
| Populations represented | 85 groups (32 tribal, 53 non-tribal) | Understanding population-specific disease risks |
| Sample size | 9,772 individuals (after quality control) | Statistically powerful dataset for rare variants |
| Data repository | Indian Biological Data Centre (IBDC) | Resource for global research community 7 |
Dr. Kumarasamy Thangaraj, one of the project leaders, explained: "We are looking for variants which are functionally relevant—related to diseases, those associated with therapeutic responses or no responses, and those that are causing adverse effects to therapeutic agents" 7 .
Behind every genomic discovery lies an array of specialized tools—both wet-lab reagents and dry-lab computational solutions. Here are the essential components powering this research revolution:
| Tool Category | Specific Examples | Function |
|---|---|---|
| Sequencing Technologies | Illumina NovaSeq, Oxford Nanopore | Determine the order of nucleotides in DNA/RNA molecules |
| Bioinformatics Pipelines | BWA, GATK, Cell Ranger | Process raw sequencing data into analyzable formats |
| Data Visualization Tools | Tableau, Canva, Genomic Browsers | Create engaging visual representations of complex data 6 |
| Programming Languages | Python, R, Bash | Develop custom analyses and automate workflows |
| Specialized Databases | Indian Biological Data Centre (IBDC), NCBI | Store and retrieve genomic information 7 |
| Computational Environments | Jupyter Notebooks, Galaxy Project | Interactive analysis and reproducible research |
The future of bioinformatics and genomics shines with possibilities, many being shaped by Indian-origin scientists in key leadership roles. The field is rapidly evolving toward:
Machine learning algorithms detecting patterns in genomic data that escape human observation 9 .
Examining genetic activity in individual cells rather than bulk tissue 9 .
Combining genomic data with proteins, metabolites, and environmental factors.
Virtual reality environments to explore molecular structures in 3D .
As Dr. Todd Treangen of Rice University notes, "ASM BIG recognizes that the microbial sciences are experiencing a data revolution. Our goal is to convene the researchers, clinicians and data experts who are not only generating microbial data, but also transforming it into scientific advances that address global challenges" 2 .
The story of Indian-origin scientists in bioinformatics and genomics is more than a tale of individual achievement—it's about building bridges between cultures, disciplines, and data domains.
From improving crops to advancing medicine
Building on Khorana's legacy while mentoring new generations
Fusing computational sophistication with biological insight
As we continue to unravel the complexities of life through data, this vibrant scientific community will undoubtedly play an essential role in writing the next chapter of biological discovery—one line of code, one genetic variant, and one breakthrough at a time.