Josip S. Herman

About

Josip S. Herman is a computational biologist whose work has significantly advanced the understanding of cellular decision-making through single-cell genomics. His primary research focuses on developing and applying computational methods to decode cell fate specification from high-throughput single-cell RNA sequencing (scRNA-seq) data. Herman’s most impactful contribution is the creation of FateID, a computational framework that infers cell fate bias in multipotent progenitors directly from scRNA-seq data. This tool, detailed in his 2018 paper which has garnered 384 citations, enables researchers to predict lineage choices before overt differentiation, providing a powerful lens into developmental biology and stem cell dynamics. Additionally, his work on high-throughput scRNA-seq data analysis pipelines (2018, 23 citations) has helped standardize the processing of complex single-cell datasets. By bridging computational innovation with biological discovery, Herman’s research empowers the scientific community to explore how individual cells commit to distinct identities, with implications for regenerative medicine and cancer biology. His contributions exemplify how method development can unlock new dimensions of cellular heterogeneity and fate mapping.

Research Focus

Key Achievements

Top Papers

1. 1
   FateID infers cell fate bias in multipotent progenitors from single-cell RNA-seq data

   384 citations · 2018
2. 2
   High-Throughput Single-Cell RNA Sequencing and Data Analysis

   23 citations · 2018

Key Collaborators

Contact & Links