Manish Kumar

Bioinformatics Programmer · University of Kansas Medical Center

Senior Computational Scientist with 18+ years of experience across healthcare, academia, and translational research in the US, Middle East, and Asia — turning large-scale multi-omics data into reproducible, clinically actionable insights.

Kansas City, KS
M.Sc Bioinformatics · Jamia Millia Islamia
MS Data Science · Eastern University

Built out of
real frustration

After 18+ years running bioinformatics pipelines across hospitals, universities, and research institutes on three continents, one problem kept repeating itself: every new project meant starting over.

Installing dozens of tools. Resolving dependency conflicts. Rebuilding pipelines from scratch. Porting workflows between local machines, HPC clusters, and cloud environments — each one behaving differently. Hours lost before a single base was aligned.

"I built OmniBioAI because I was tired of the setup getting in the way of the science. Researchers should spend their time asking biological questions — not debugging environment configurations."

OmniBioAI changes that. Upload your data, choose your pipeline, and run. Everything is already there — tools, plugins, workflow engines, and an AI reasoning layer — ready to go across any environment.

What makes it
different

Most bioinformatics platforms solve one piece of the puzzle. OmniBioAI unifies the entire stack: reproducible multi-omics pipelines, modular plugins, agentic AI orchestration, and full provenance tracking — in a single platform.

Instead of a command line and a stack of documentation, researchers get a workbench. Choose from 16+ pipeline types covering scRNA-seq, WGS, proteomics, methylation, spatial transcriptomics, drug discovery, and more.

And for exploratory analysis, there's a prompt-based AI interface. Describe what you want to find — OmniBioAI's LangGraph agent handles the rest, reasoning across tools and datasets to surface biologically meaningful insights.

Built and hosted on a self-funded home AI supercomputer — an NVIDIA DGX Spark — and now open to the research community.

18+Years experience
5Countries worked in
16+Omics pipelines built
3Peer-reviewed papers
200+Integrated tools

Experience

Bioinformatics Programmer / Research Associate
Oct 2024 – Present
University of Kansas Medical Center
Kansas City, KS
Bioinformatics Software Engineer II
Mar 2021 – Aug 2024
Children's Mercy Kansas City
Kansas City, MO
Bioinformatics IT Specialist II
Feb 2019 – Mar 2021
University of Tennessee · Oak Ridge National Laboratory
Knoxville, TN
Senior Research Specialist Bioinformatician
Sep 2014 – Sep 2017
Weill Cornell Medical College in Qatar
Doha, Qatar
Bioinformatician (Consultant)
Apr 2018 – Oct 2018
King Faisal Specialist Hospital · Saudi Genome Project
Riyadh, Saudi Arabia
Senior Bioinformatics Software Developer
Aug 2008 – Aug 2014
Synamatix Sdn Bhd
Kuala Lumpur, Malaysia
Bioinformatics Programmer
Jul 2007 – Aug 2008
Systems Biology India Pvt. Ltd.
Pune, Maharashtra, India

Publications

2025
Genetic mutations in lymphocytic variant of hypereosinophilic syndrome: study of five siblings
Frontiers in Medicine · December 2025
↗ View paper
2018
Whole Exome Sequencing identifies common and rare variant Metabolic QTLs in a Middle Eastern Population
Nature Communications · January 2018
↗ View paper
2015
MetaRNA-Seq: An Interactive Tool to Browse and Annotate Metadata from RNA-Seq Studies
BioMed Research International · August 2015
↗ View paper

Skills & stack

Built up across 18+ years of production bioinformatics and AI platform engineering.

Languages
PythonRBashPerlSQLJavaScriptC++
Workflow engines
NextflowWDLSnakemakeCWLCromwell
Genomics tools
GATKSeuratDESeq2SnpEffCell RangerBWASAMtools
AI & ML
LangGraphPyTorchHuggingFaceOllamaCUDANMF
Infrastructure
DockerKubernetesAWSAzureSlurmDNAnexus
Backend
DjangoFastAPICeleryRedisMySQL

Want to try OmniBioAI?

Join the private beta — upload your data, pick a pipeline, and run reproducible multi-omics analysis in minutes.