Yongqin Wang
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Yongqin Wang has a total of 23 co-authors. Here are the top co-authors by number of shared publications:
- Aj Ireland
Environmental Genomics and Systems Biology Division, E.O. Lawrence Berkeley National Laboratory, Berkeley, California, USA
2 shared publications - Ali Mekki Missaoui
Department of Crop and Soil Sciences University of Georgia Athens Georgia USA
2 shared publications - Angelica M. Walker
The Bredesen Center for Interdisciplinary Research and Graduate Education, University of Tennessee Knoxville
2 shared publications - Anna Furches
334 Math & Natural Science Building, Department of Biology, Lincoln Memorial University, 6965 Cumberland Gap Parkway, Harrogate, Tennessee 37752 USA
2 shared publications - Ashley Cliff
The Bredesen Center for Interdisciplinary Research and Graduate Education, University of Tennessee Knoxville
2 shared publications - D. Dakota Blair
Artificial Intelligence Department, Brookhaven National Laboratory, Upton, New York, USA
2 shared publications
Latest Publications
- Open Access
- 6 January 2025
- Published by Oxford University Press (OUP) in GigaScience
- Vol. 14
RWRtoolkit: multi-omic network analysis using random walks on multiplex networks in any species
We introduce RWRtoolkit, a multiplex generation, exploration, and statistical package built for R and command-line users. RWRtoolkit enables the efficient exploration of large and highly complex biological networks generated from custom experimental data and/or from publicly available datasets, and is species agnostic. A range of functions can be used to find topological distances between biological entities, determine relationships within sets of interest, search for topological context around sets of interest, and statistically evaluate the strength of relationships within and between sets. The command-line interface is designed for parallelization on high-performance cluster systems, which enables high-throughput analysis such as permutation testing. Several tools in the package have also been made available for use in reproducible workflows via the KBase web application.
- 6 January 2025
- Published by Oxford University Press (OUP) in GigaScience
- Vol. 14
Open AccessRWRtoolkit: multi-omic network analysis using random walks on multiplex networks in any species
We introduce RWRtoolkit, a multiplex generation, exploration, and statistical package built for R and command-line users. RWRtoolkit enables the efficient exploration of large and highly complex biological networks generated from custom experimental data and/or from publicly available datasets, and is species agnostic. A range of functions can be used to find topological distances between biological entities, determine relationships within sets of interest, search for topological context around sets of interest, and statistically evaluate the strength of relationships within and between sets. The command-line interface is designed for parallelization on high-performance cluster systems, which enables high-throughput analysis such as permutation testing. Several tools in the package have also been made available for use in reproducible workflows via the KBase web application.
- Open Access
RWRtoolkit: multi-omic network analysis using random walks on multiplex networks in any species
Leveraging the use of multiplex multi-omic networks, key insights into genetic and epigenetic mechanisms supporting biofuel production have been uncovered. Here, we introduce RWRtoolkit, a multiplex generation, exploration, and statistical package built for R and command line users. RWRtoolkit enables the efficient exploration of large and highly complex biological networks generated from custom experimental data and/or from publicly available datasets, and is species agnostic. A range of functions can be used to find topological distances between biological entities, determine relationships within sets of interest, search for topological context around sets of interest, and statistically evaluate the strength of relationships within and between sets. The command-line interface is designed for parallelisation on high performance cluster systems, which enables high throughput analysis such as permutation testing. Several tools in the package have also been made available for use in reproducible workflows via the KBase web application.
Open AccessRWRtoolkit: multi-omic network analysis using random walks on multiplex networks in any species
Leveraging the use of multiplex multi-omic networks, key insights into genetic and epigenetic mechanisms supporting biofuel production have been uncovered. Here, we introduce RWRtoolkit, a multiplex generation, exploration, and statistical package built for R and command line users. RWRtoolkit enables the efficient exploration of large and highly complex biological networks generated from custom experimental data and/or from publicly available datasets, and is species agnostic. A range of functions can be used to find topological distances between biological entities, determine relationships within sets of interest, search for topological context around sets of interest, and statistically evaluate the strength of relationships within and between sets. The command-line interface is designed for parallelisation on high performance cluster systems, which enables high throughput analysis such as permutation testing. Several tools in the package have also been made available for use in reproducible workflows via the KBase web application.