Niko Välimäki

OMIDIENT is a multi-omics integration method that uses Dirichlet auto-encoders to improve clustering, classification, and data reconstruction across cancer types.

The paper identifies a phosphorylation switch in PAGE4 as a key mechanism in MED12-mutant fibroid pathogenesis, revealing its role in rewiring the interactome and transcriptional machinery.

This study identifies retrotransposon insertions in colorectal tumors, linking them to cancer initiation and poor patient survival.

This study identifies five new genetic loci associated with uterine leiomyoma risk and links them to estrogen receptor alpha and genetic stability.

The paper analyzes genome sequences of Campylobacter jejuni isolates to assess genetic similarity and spatial-temporal patterns within a clonal complex, finding monomorphic clones with global dispersion potential.

This paper introduces SEER, a statistical method to identify sequence elements associated with bacterial phenotypes, demonstrating its application in discovering antibiotic resistance and invasiveness factors in Streptococcus species.

The paper enhances variation detection by using pan-genome indexing to create a recombined reference sequence from multiple alignments, improving detection on real datasets.