White papers and other resources

September 3, 2025
White Paper
Genialis™ krasID White Paper
February 10, 2024
White Paper
RNA: the Future of Predictive Biomarkers
December 13, 2023
Tutorial
Normalizing RNA-seq data in Python with RNAnorm

Scientific journals

March 20, 2026
PLoS One
Visual analytics framework for survival analysis and biomarker discovery from gene expression data
June 9, 2025
Artificial Intelligence in Medicine
Large scale gene set ranking for survival-related gene sets
February 19, 2024
European Journal of Pharmaceutical Sciences
Transcriptome analysis reveals involvement of thiopurine S-methyltransferase in oxidation-reduction processes
May 23, 2023
Frontiers in Oncology
Xerna™ TME Panel is a machine learning-based transcriptomic biomarker designed to predict therapeutic response in multiple cancers

Conference posters

April 3, 2026
AACR 2026
An RNA-based survival model predicting real-world response to trastuzumab deruxtecan
December 1, 2025
CELCC 2025
Frequency of driver mutations across disease stages in Slovenian non-small cell lung cancer patients
November 12, 2025
ESMO AI 2025
A large molecular model (LMM)-based predictor of clinical response to the WEE1 inhibitor Debio 0123 + carboplatin therapy
October 18, 2025
ESMO 2025
The frequency of driver alterations in non-small cell lung cancer patients: Slovenian nationwide observational cohort trial
July 21, 2025
ISMB/ECCB 2025
Assessing confidence in genetic variants identified in RNA-seq data
May 30, 2025
ASCO 2025
Prediction of sotorasib response duration and identification of clinically actionable resistance mechanisms using an RNA-based patient classifier
April 17, 2025
AACR 2025
Genialis™ Supermodel: Predicting monotherapy and combination therapy responses in KRAS-mutated cancers using a large molecular model of cancer biology
April 17, 2025
AACR 2025
Biology-driven, machine learning-based development of a biomarker to predict response to WEE1 inhibitor Debio 0123

Sean Khozin on pre-competitive collaboration, data sharing, and AI in oncology, and how these efforts advance cancer research and innovation. Listen to TPM episode 54 →

Sean Khozin on pre-competitive collaboration, data sharing, and AI in oncology, and how these efforts advance cancer research and innovation. Listen to TPM episode 54 → Sean Khozin on pre-competitive collaboration, data sharing, and AI in oncology, and how these efforts advance cancer research and innovation. Listen to TPM episode 54 →

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