Computational Biology · Plant-Microbe Genomics · Open Science
I build open computational tools to understand how plants and microbes interact — from genome assembly and co-expression networks to field-deployable sequencing platforms.
I am a computational biologist specialising in plant-microbe genomics, alternative splicing, and transcriptomics. As Postdoctoral Researcher at TUM Weihenstephan and Helmholtz Munich, I serve as the bioinformatics core for the TRR 356 collaborative research initiative — providing analytical infrastructure and pipeline support for 8+ research groups across TUM, LMU, Tübingen, and MPI.
My PhD at TUM (2019–2022) focused on reproducibility in alternative splicing analysis, resulting in DICAST — an open benchmarking platform that was used on clinical RNA-seq datasets. That commitment to reproducible, open methodology shapes every project I take on.
Outside academia, I co-founded Sentry Bio, applying metagenomic sequencing and ML-based taxonomic classification to autonomous pathogen detection and environmental biosurveillance.
Analysed differentially expressed genes at translocation breakpoints within the hexaploid oat pangenome — investigating whether structural genomic rearrangements drive transcriptional changes across diverse varieties.
Python-based open benchmarking platform for 20+ RNA splicing detection methods across clinical RNA-seq datasets. Lead developer, coordinating a team of 5. The reference benchmark in its domain.
Developed a custom NVIDIA Jetson-based compute module paired with Oxford Nanopore Mk1B for real-time basecalling and metagenomic sequencing of environmental microbial communities in the field.
Pipeline infrastructure and HPC resource management supporting 8+ research groups across TUM, LMU, Tübingen and MPI — investigating plant-microbe interactions at scale.
Benchmarking platform for alternative splicing detection. 20+ tools evaluated across standardised RNA-seq datasets. Built for reproducibility from the ground up.
Documentation →Hands-on workshop covering pipeline execution, configuration, and HPC best practices for reproducible workflows. Run for the TRR356 consortium on LRZ infrastructure.
View materials →Tree inference, comparative genomics, and evolutionary analysis of plant and microbial genomes. Developed for the TRR356 consortium.
40-hour practical course co-developed and delivered at TUM over 4 semesters, ~30 students per cohort. RNA-seq end-to-end on de.NBI cloud infrastructure.
Contributed the lrz_cm4 institutional configuration
to nf-core/configs (PR #981), enabling seamless pipeline execution
on LRZ CM4 HPC for the community.
Pipeline infrastructure and support for 8+ research groups. Analytical workflows for dual-species RNA-seq, pangenomics, and co-expression network analysis.
Sentry Bio is an autonomous biosurveillance platform I co-founded, applying the same metagenomic sequencing and ML-based taxonomic classification methods from my research to real-world pathogen detection.
We are building foundation model pretraining pipelines for metagenomic sequence analysis — trained on environmental DNA to detect, classify, and track microbial communities in near real-time using nanopore sequencing.
The motivation comes from a gap we observed in research contexts — field-deployable sequencing exists, but the analytical layer rarely travels with it. Sentry Bio is building that layer: lightweight, reproducible, and designed to run where the samples are.
Visit Sentry Bio →Complete CV with publications, teaching, and conference contributions.
Download CV (PDF)Reach out depending on what brought you here.
TRR 356, plant-microbe genomics, RNA-seq analysis, nf-core pipelines, WGCNA, pangenomics, or teaching.
amit.fenn@tum.dePathogen detection, environmental monitoring, nanopore sequencing deployments, or investor inquiries.
amit@sentry.bio