Intro on Q-omics data mining

  - Consensus scores in associated data?

  - Ad-hoc analysis: AI-assisted "text-to-data mining"

  - Functional analysis: gene ontology & GSEA scores

  - Advanced feature: tumor-specific surface genes and neoantigens

  - Advanced feature: synthetic lethal gene pairs

  - Advanced feature: Pembrolizumab treatment response


Analysis example

  - Molecular features associated with poor prognosis in breast cancer

  - Tumor Microenvironment in Breast Cance


Metrics on graphs

  - Terms (responder vs. non-responder) describing patient drug treatment

  - Fold-change & p-value

  - X/Y-scores & cross-association between data pair

  - AUCs in Kaplan-Meier plot (survival analysis)

  - CRISPR/shRNA efficacy, drug response (-logGI50)

Poster download

Q-omics has recently been showcased at premier international conferences, including Bio-IT World (Boston), EACR (Lisbon), ISMB/ECCB (Liverpool) and FCS (Singapore)

Q-omics publications

- Bridging literature and omics: Q-omics 3 integrates LLM-guided text-to-data workflows and pan-cancer multi-omics consensus       scoring, 2026, In preparation

 - NetCrafter: Ontology-derived Gene Network Modeling and Functional Interpretation, 2026, Briefings in Bioinformatics

- Current advances in comprehensive omics data mining for oncology and cancer research, 2024, Biochim Biophys Acta Rev         Cancer

- Q-omics: Smart Software for Assisting Oncology and Cancer Research, 2021, Mol. Cells

- QCanvas: a graphical user interface for data clustering and visualization, 2012, Genomics Inform