The feasibility of genome-scale biological network inference using Graphics Processing Units. - Raghuram Thiagarajan; Amir Alavi; Jagdeep T. Podichetty; Jason N. Bazil; Daniel A. Beard (Algorithms Mol. Biol., 2017)

Insights into Performance Fitness and Error Metrics for Machine Learning. - M. Z. Naser; Amir Alavi (CoRR, 2020)

Iterative point set registration for aligning scRNA-seq data. - Amir Alavi; Ziv Bar-Joseph (PLoS Comput. Biol., 2020)

Hummingbird: efficient performance prediction for executing genomic applications in the cloud. - Amir Bahmani; Ziye Xing; Vandhana Krishnan; Utsab Ray; Frank Mueller 001; Amir Alavi; Philip S. Tsao; Michael P. Snyder; Cuiping Pan (Bioinform., 2021)

Swarm: A federated cloud framework for large-scale variant analysis. - Amir Bahmani; Kyle Ferriter; Vandhana Krishnan; Arash Alavi 003; Amir Alavi; Philip S. Tsao; Michael P. Snyder; Cuiping Pan (PLoS Comput. Biol., 2021)

Supervised Adversarial Alignment of Single-Cell RNA-seq Data. - Songwei Ge; Haohan Wang; Amir Alavi; Eric P. Xing; Ziv Bar-Joseph (J. Comput. Biol., 2021)