Integration Of Multiple Datasets
Integration of Multiple Datasets is a computational methodology in single-cell RNA sequencing analysis that enables the joint analysis of distinct datasets by correcting batch effects and aligning biological states across experiments while preserving biological variability.
720
Publications
105.7K
Citations
5.3K
Authors
1.6K
Institutions
Publications per year
2017–2026
488
720
Integrated analysis of multimodal single-cell data
Yuhan Hao, Stephanie Hao, Erica Andersen‐Nissen et al. · Cell · 2021 · 16K citations · Full text
MultiQC: summarize analysis results for multiple tools and samples in a single report
Philip Ewels, Måns Magnusson, Sverker Lundin et al. · Bioinformatics · 2016 · 10.4K citations · Full text
MoleculeNet: a benchmark for molecular machine learning
Zhenqin Wu, Bharath Ramsundar, Evan N. Feinberg et al. · Chemical Science · 2017 · 2.9K citations · Full text
Atray Dixit, Oren Parnas, Biyu Li et al. · Cell · 2016 · 1.9K citations · Full text
1–5 of 720
5.3K
7
h-index
7
h-index
7
h-index
6
h-index
5
h-index
1–5 of 5.3K
1.6K
Harvard University
Cambridge, United States
23 h-index
175 publications
31K citations
Stanford University
Stanford, United States
22 h-index
117 publications
93.7K citations

Chinese Academy of Sciences
Beijing, China
21 h-index
169 publications
11.2K citations
University of Chinese Academy of Sciences
Beijing, China
17 h-index
127 publications
7.3K citations
University of Oxford
Oxford, United Kingdom
16 h-index
63 publications
9.4K citations
Tsinghua University
Beijing, China
16 h-index
30 publications
3.3K citations
University of Michigan
Ann Arbor, United States
14 h-index
40 publications
5.6K citations

University of British Columbia
Vancouver, Canada
14 h-index
33 publications
1.7K citations
1–8 of 1.6K
49 publications · 16.4K citations
31
h-index
28 publications · 4.5K citations
26
h-index
Repository · 50 publications · 3.4K citations
24
h-index
24 publications · 2.6K citations
22
h-index
22 publications · 2.5K citations
20
h-index
1–5