Text-based querying allows for more flexible and creative data mining than fixed menus.
We have developed an ad-hoc module by training large language models (LLMs) such as GPT, BERT, and RoBERTa to interpret user queries and generate data mining workflows for Q-omics data analysis, requiring no computational skills.
* The ad hoc LLM module is still under developing, and an advanced version will be available soon
* Example queries (Copy and paste an example query to "Ad-hoc" analysis window)
1) How is glucose starvation associated with cancer progression?
2) BRCA patient survival in different stages of cancer progression
3) Synthetic lethality of ITGAV and MDFI genes