Quaid Morris

Quaid Morris is an Assistant Professor at Weill Cornell Medicine's Graduate School of Medical Sciences, where he leads a research laboratory focused on applying computational approaches to biomedical problems. His lab is affiliated with the Physiology, Biophysics & Systems Biology program and has strong ties to the Sloan Kettering Institute.

Dr. Morris's research spans multiple areas of computational biology with a particular emphasis on cancer genomics and post-transcriptional regulation. His work integrates machine learning with biological data to address fundamental questions in tumor evolution, RNA-binding protein specificity, and genotype-phenotype relationships. His laboratory develops innovative computational methods to reconstruct tumor evolutionary histories, predict RNA-binding protein targets, and integrate diverse biological data sources.

Analysis of Dr. Morris's recent publications (2021-2023) reveals a strong focus on cancer genomics, particularly in tumor evolution and mutational signature analysis, alongside continued work on RNA-binding proteins and their regulatory roles. His research demonstrates a consistent pattern of developing computational tools (such as Pairtree and TrackSig) that address specific challenges in analyzing complex biological data, with applications spanning basic science to clinical translation.

Dr. Morris has mentored numerous graduate students, postdoctoral fellows, and undergraduate researchers who contribute to his diverse research portfolio. His laboratory maintains active development of open-source software tools that have been widely adopted by the computational biology community.

The Morris lab actively collaborates with experimental biologists to validate computational predictions and translate findings into biological insights. Current research directions include applying machine learning to electronic medical records for clinical prediction, developing methods for single-cell data analysis, and exploring the role of RNA-binding proteins in disease mechanisms.