output
20092024
most citedGuidelines for the next 10 years of proteomics

249 citations

6 papers

quant-ph2024★ 5 cited

Robust Quantum Reservoir Computing for Molecular Property Prediction

Daniel Beaulieu, Milan Kornjaca, Zoran Krunic +4

Machine learning has been increasingly utilized in the field of biomedical research to accelerate the drug discovery process. In recent years, the emergence of quantum computing ha…

quant-ph2022★ 61 cited

Quantum kernels for real-world predictions based on electronic health records

Zoran Krunic, Frederik F. Flöther, George Seegan +2

In recent years, research on near-term quantum machine learning has explored how classical machine learning algorithms endowed with access to quantum kernels (similarity measures)…

cs.LG2021★ 2 cited

Machine Learning Applications for Therapeutic Tasks with Genomics Data

Kexin Huang, Cao Xiao, Lucas M. Glass +3

Thanks to the increasing availability of genomics and other biomedical data, many machine learning approaches have been proposed for a wide range of therapeutic discovery and devel…

q-bio.OT2020

Healthcare Utilization and Perceived Health Status from Falun Gong Practitioners in Taiwan: A Pilot SF-36 Survey

Yu-Whuei Hu, Li-Shan Huang, Eric J. Yeh +1

Objective: Falun Gong (FLG) is a practice of mind and body focusing on moral character improvement along with meditative exercises. This 2002 pilot study explored perceived health…

q-bio.OT2020

Clinical Trial Drug Safety Assessment for Studies and Submissions Impacted by COVID-19

Mary Nilsson, Brenda Crowe, Greg Anglin +4

In this paper, we provide guidance on how standard safety analyses and reporting of clinical trial safety data may need to be modified, given the potential impact of the COVID-19 p…

q-bio.GN2009★ 249 cited

Guidelines for the next 10 years of proteomics

Marc R Wilkins, Ron D Appel, Jennifer E Van Eyk +13

In the last ten years, the field of proteomics has expanded at a rapid rate. A range of exciting new technology has been developed and enthusiastically applied to an enormous varie…