Faisal Alquaddoomi

The paper introduces CytoTable, a software package that harmonizes single-cell image-based profiling data from different tools, enabling reproducible and scalable data integration.

The paper introduces hetnet connectivity search to find meaningful relationships between biomedical entities in heterogeneous networks without requiring supervised training data.

scROSHI identifies cell types without training data by using pre-existing gene sets and hierarchical relationships, outperforming methods in low-data and high-diversity scenarios.

MolEvolvR provides a web-app for analyzing protein evolution through phylogenetic context, offering tools to explore conserved domains, lineage-specific variants, and domain architectures.

SCIM matches single-cell measurements across technologies by learning a technology-invariant latent space and applying bipartite matching, achieving high accuracy in real-world datasets.