
Ornella Cominetti
Nestlé Institute of Food Safety and Analytical Sciences (NIFSAS), Proteomics Group
Ornella Cominetti is a Senior Omics Data Specialist in the Proteomics laboratory at the Nestlé Institute of Food Safety and Analytical Sciences (Nestlé Research, Lausanne, Switzerland). She holds a PhD from the University of Oxford and a Biotechnology Engineering Degree from the University of Chile.

Marie Pier Scott-Boyer
CHU de Québec-Université Laval
Marie Pier Scott-Boyer is a research associate in the computational biology laboratory at the CHU de Québec-Université Laval Research Center. She holds a PhD in bioinformatics from Université de Montréal (2013) and an MBA from Université Laval (2021). Her research activities cover different aspects of system biology using multi-omics data from human clinical trials. Ongoing projects include 1) integration of multi-omics longitudinal data 2) high throughput data analysis and network analysis for bioactive efficacy and toxicology, and 3) management strategies for the integration of data from diverse experimental sources.
This Methods Collection aims to provide a step-by-step guide on how to apply multi-omics integration in practice using case studies and real data. We invite submissions of novel tools and applications of well-known methodologies in the field of multi-omics. The purpose is to showcase a variety of tools and environments for multi-omics integration, including R (packages like mixomics), Python, Qlucore, and many others.
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Cited by 3
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2024
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Corinna Losert1,2, Kami Pekayvaz3,4, Viktoria Knottenberg3,4, Leo Nicolai3,4, Konstantin Stark3,4, Matthias Heinig1,2,4
1Institute of Computational Biology, German Research Center for Environmental Health, Helmholtz Zentrum München, 2Department of Computer Science, TUM School of Computation, Information and Technology, Technical University of Munich, 3Medizinische Klinik und Poliklinik I University Hospital Ludwig-Maximilian University, 4German Centre for Cardiovascular Research (DZHK), partner site Munich Heart Alliance
Multi-omic single-cell velocity models epigenome–transcriptome interactions and improves cell fate prediction
Chen Li1,
Joshua Welch*1,
Maria Virgilio1,
Kathleen Collins1
1University of Michigan