Stefano Lonardi, PhD, University of California, Riverside, USA
Oluwatosin Oluwadare, PhD, University of Colorado, Colorado Springs, USA
name, qualification, affiliation, country
BMC Bioinformatics is welcoming submissions to our Collection on 3D genomics. This Collection welcomes submissions on the development of novel computational and statistical approaches for the analysis of 3D genomics data.
Stefano Lonardi, PhD, University of California, Riverside, USA
Stefano Lonardi is Professor and Vice Chair for Undergraduate Education in the Department of Computer Science and Engineering at University of California, Riverside, CA. His research interests include computational molecular biology, bioinformatics, genetics, epigenetics and genomics, design of algorithms, and data science. He is a NSF CAREER recipient (2005), Fellow of the IEEE (2016), ACM Distinguished Scientist (2017) and Fellow of AAAS (2018). In 2021, he was the recipient of the NIH Director's Transformative Research Award. His research program has been supported by NSF, NIH, DOE, DARPA, US-AID and USDA.
Oluwatosin Oluwadare, PhD, University of Colorado, Colorado Springs and University of Colorado School of Medicine, USADr Oluwatosin Oluwadare is an Assistant Professor of Computer Science and Innovation at the University of Colorado, Colorado Springs (UCCS), with a secondary appointment in the Department of Biomedical Informatics at the University of Colorado School of Medicine, Anschutz Medical Campus. His lab focuses on Deep Learning in Bioinformatics, developing advanced algorithms and tools to analyze large-scale biological datasets. His research areas include 3D Chromosome and Genome Structure Modeling, Hi-C Data Resolution Enhancement, and TAD/Chromatin Loop Detection, with an emphasis on leveraging machine learning to address complex biological challenges. His work is supported by funding from the U.S. National Science Foundation and the National Institutes of Health.
[name, qualification(s), affiliation, country][bio]
BMC Bioinformatics is welcoming submissions to our Collection on 3D genomics.
Three-dimensional genomics (3D genomics) offers comprehensive insights into the spatial organization of the genome within the cell nucleus, facilitating the study of chromatin architecture, genome folding, and their implications for gene regulation and cellular function. This field has become essential for understanding the topological and functional relationships within the genome, identifying novel chromatin interactions and elucidating the regulatory mechanisms underpinning genomic organization.
This Collection welcomes submissions on the development of novel computational and statistical approaches for the analysis of 3D genomics data. We are particularly interested in innovative approaches that address challenges in modeling chromatin interactions and integrating multi-dimensional genomic data.
Image credit: © [M] petarg / stock.adobe.com
There are currently no articles in this collection.
This Collection welcomes submission of original research, software and database articles. Should you wish to submit a different article type, please read our submission guidelines to confirm that type is accepted by the journal. Articles for this Collection should be submitted via our submission system, Snapp. During the submission process you will be asked whether you are submitting to a Collection, please select "3D genomics" from the dropdown menu.
Articles will undergo the journal’s standard peer-review process and are subject to all of the journal’s standard policies. Articles will be added to the Collection as they are published.
The Editors have no competing interests with the submissions which they handle through the peer review process. The peer review of any submissions for which the Editors have competing interests is handled by another Editorial Board Member who has no competing interests.