Robert J. Millikin

This paper introduces KM-GPT-DCH, a method using LLMs and Bayesian analysis to evaluate and compare biomedical hypotheses by analyzing scientific literature.

SKiM-GPT evaluates biomedical hypotheses by combining literature-based discovery with large language models to assess hypothesis validity using retrieved PubMed abstracts.

SKiM discovers and annotates biomedical knowledge using co-occurrence and transformer models to find A-B-C relationships between user-defined concepts.

This study identifies FUS's role in DNA replication timing and progression, showing its importance in genome stability and its potential contribution to disease.

Spritz generates sample-specific proteogenomic databases annotated with sequence variations and PTMs from RNA-seq data, enabling improved identification of proteoforms in mass spectrometry analyses.

The paper evaluates and implements two label-free quantification tools in the Galaxy platform for proteomics and multi-omics analysis.