Discovery, in print.

01

bioRxiv / October 13, 2026 · Preprint, not peer reviewed

Co-First Author

Decoding protein–RNA interactions with eclair CLIP and Pythia

We developed eclair CLIP (ecCLIP), a high-throughput platform that generated a high-resolution binding atlas for 67 endogenously tagged RNA-binding proteins in HEK293T cells. The atlas improved RNA stability modeling with Borzuki and supported Pythia, a structure-aware model of protein–RNA recognition. Massively parallel reporter CLIP assays tested sequence, structure, and variant effects on binding for five RBPs.

Karimzadeh M†, Fish L†, Karner H†, Linder J†, Emadi A†, Hernandez-Corchado A, Smaili FZ, Ghavami K, Stewart ES, Kelley D, Wang B, Najafabadi HS, Leonetti MD, Goodarzi H. (2026). A high-resolution protein-RNA binding atlas for structure-aware interaction prediction and post-transcriptional regulatory modeling. bioRxiv. doi: 10.64898/2026.10.12.758580.

02

Science Advances / 2026

Co-First Author

An RNA stability program that suppresses metastasis

We systematically measured mRNA stability across diverse breast cancer models and built GreyHound, an interpretable deep-learning framework to identify regulators of RNA decay. This work revealed that RBMS3 stabilizes a metastasis-suppressive transcript program centered on TXNIP, linking post-transcriptional regulation directly to breast cancer progression.

Karner H†, Mittmann TC†, Chen VW, Borah AA, Langen A, Yousefi H, Fish L, Zaro BW, Navickas A, Goodarzi H. (2026). Integrative analysis of mRNA stability regulation uncovers a metastasis-suppressive program in breast cancer. Science Advances 12, eaea9061.

03

Patterns / 2024

Co-First Author

Deep learning meets microRNA drug discovery

We developed RiboStrike, a deep-learning framework that identified small molecules with anti-miR-21 activity. I contributed to the experimental validation, helping test candidate compounds through reporter assays and RNA-seq and showing that the top hit reduced lung metastases in a breast cancer mouse model.

Keshavarzi Arshadi A†, Salem M†, Karner H†, Garcia K, Arab A, Yuan JS, Goodarzi H. (2024). Functional microRNA-targeting drug discovery by graph-based deep learning. Patterns 5, 100909.

04

Journal of Molecular Biology / 2020

First Author · Featured Article · Cover Art

Conserved RNA function across divergent sequences

I showed that the human lncRNA JPX remains functionally conserved despite major sequence and structural divergence from mouse Jpx: it still binds CTCF and can rescue Xist-related defects in mouse embryonic stem cells.

Karner HM, Webb CH, Carmona S, Liu Y, Lin B, Erhard M, Chan D, Baldi P, Spitale RC, Sun S. (2020). Functional Conservation of LncRNA JPX Despite Sequence and Structural Divergence. Journal of Molecular Biology 432:283-300.