This study extends a gene pair classification method to ordinal outcomes, showing comparable performance with higher interpretability in glioblastoma and ovarian cancer.

Bioinformatics Advances · Jan 1, 2026Peer-reviewedSystems Biology

Multi-Omics Analysis Reveals the Attenuation of the Interferon Pathway as a Driver of Chemo-Refractory Ovarian Cancer

Daria Afenteva, Rong Yu, Anna Rajavuori, Marina Salvadores, Inga-Maria P. Launonen, Kari Lavikka, Kaiyang Zhang, Anna Pirttikoski, Giovanni Marchi, Sanaz Jamalzadeh, Veli‐Matti Isoviita, Yilin Li, Giulia Micoli, Erdoğan Pekcan Erkan, Matías Marín Falco, , Sampsa Hautaniemi

The paper identifies reduced IFN-I pathway activity as a driver of chemo-refractory ovarian cancer using multi-omics analysis in a clinical trial cohort.

Cell Reports Medicine · Aug 29, 2025Peer-reviewedCancer Biology

Multi-modal characterization of transcriptional programs that drive metastatic cascades to solid sites and ascites in ovarian cancer

Kaiyang Zhang, Essi Kahelin, Giovanni Marchi, Oskari Lehtonen, Shams Salloum, Kari Lavikka, Yilin Li, Felix Dietlein, Alexandra Lahtinen, Jaana Oikkonen, Sakari Hietanen, Johanna Hynninen, Antti Häkkinen, Anni Virtanen, Sampsa Hautaniemi

The paper identifies nine transcriptional programs driving metastasis in ovarian cancer using multi-modal data from 350 tumor samples, highlighting intra-patient heterogeneity and therapeutic implications.

bioRxiv · Aug 26, 2025 · PreprintCancer Biology

miQC: An adaptive probabilistic framework for quality control of single-cell RNA-sequencing data

Ariel A. Hippen, Matías Marín Falco, Lukas M. Weber, Erdoğan Pekcan Erkan, Kaiyang Zhang, Jennifer A. Doherty, Anna Vähärautio, Casey S. Greene, Stephanie C. Hicks

miQC is a probabilistic framework that jointly models mitochondrial DNA and gene detection metrics to improve single-cell RNA-seq quality control.

PLoS Computational Biology · Aug 24, 2021Peer-reviewedGenomics