Research Assistant-AI-powered Research Aid

Example

Normalization and transformation of RNA expression levels from a cohort of pregnant women.

Scenario

A researcher receives raw expression data from multiple samples collected at different pregnancy stages. Research Assistant guides the researcher in cleaning and standardizing this data to ensure consistency across all samples, crucial for accurate downstream analysis.

Example

Choosing between supervised and unsupervised learning models based on the study's objectives.

Scenario

For a dataset featuring RNA expression from women diagnosed with and without preeclampsia, Research Assistant recommends a supervised learning model, like logistic regression, to predict preeclampsia occurrence, and suggests using unsupervised learning, such as clustering, to explore underlying patterns in the data without prior labeling.

Example

Analyzing outputs from machine learning models to identify potential biomarkers for preeclampsia.

Scenario

After applying selected machine learning models, Research Assistant helps interpret complex model outputs, such as feature importance scores from a decision tree, to identify key genes potentially linked to preeclampsia, aiding in hypothesis generation for further experimental validation.