A citation-based method for searching scientific literature


List of co-cited articles
articles co-cited >1



Times Cited
  Times     Co-cited
Similarity


Comprehensive Integration of Single-Cell Data.
Tim Stuart, Andrew Butler, Paul Hoffman, Christoph Hafemeister, Efthymia Papalexi, William M Mauck, Yuhan Hao, Marlon Stoeckius, Peter Smibert, Rahul Satija. Cell 2019
100

Semisoft clustering of single-cell data.
Lingxue Zhu, Jing Lei, Lambertus Klei, Bernie Devlin, Kathryn Roeder. Proc Natl Acad Sci U S A 2019
24
100

A Single-Cell Transcriptomic Atlas of Human Neocortical Development during Mid-gestation.
Damon Polioudakis, Luis de la Torre-Ubieta, Justin Langerman, Andrew G Elkins, Xu Shi, Jason L Stein, Celine K Vuong, Susanne Nichterwitz, Melinda Gevorgian, Carli K Opland,[...]. Neuron 2019
109
100


Integrating single-cell transcriptomic data across different conditions, technologies, and species.
Andrew Butler, Paul Hoffman, Peter Smibert, Efthymia Papalexi, Rahul Satija. Nat Biotechnol 2018
100

A Single-Cell Transcriptomic Map of the Human and Mouse Pancreas Reveals Inter- and Intra-cell Population Structure.
Maayan Baron, Adrian Veres, Samuel L Wolock, Aubrey L Faust, Renaud Gaujoux, Amedeo Vetere, Jennifer Hyoje Ryu, Bridget K Wagner, Shai S Shen-Orr, Allon M Klein,[...]. Cell Syst 2016
421
100

Population structure and eigenanalysis.
Nick Patterson, Alkes L Price, David Reich. PLoS Genet 2006
100

Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells.
Florian Buettner, Kedar N Natarajan, F Paolo Casale, Valentina Proserpio, Antonio Scialdone, Fabian J Theis, Sarah A Teichmann, John C Marioni, Oliver Stegle. Nat Biotechnol 2015
565
100

Simulating multiple faceted variability in single cell RNA sequencing.
Xiuwei Zhang, Chenling Xu, Nir Yosef. Nat Commun 2019
21
100

Single-cell messenger RNA sequencing reveals rare intestinal cell types.
Dominic Grün, Anna Lyubimova, Lennart Kester, Kay Wiebrands, Onur Basak, Nobuo Sasaki, Hans Clevers, Alexander van Oudenaarden. Nature 2015
592
100

SC3: consensus clustering of single-cell RNA-seq data.
Vladimir Yu Kiselev, Kristina Kirschner, Michael T Schaub, Tallulah Andrews, Andrew Yiu, Tamir Chandra, Kedar N Natarajan, Wolf Reik, Mauricio Barahona, Anthony R Green,[...]. Nat Methods 2017
482
100

Integration and transfer learning of single-cell transcriptomes via cFIT.
Minshi Peng, Yue Li, Brie Wamsley, Yuting Wei, Kathryn Roeder. Proc Natl Acad Sci U S A 2021
3
100


Visualization and analysis of single-cell RNA-seq data by kernel-based similarity learning.
Bo Wang, Junjie Zhu, Emma Pierson, Daniele Ramazzotti, Serafim Batzoglou. Nat Methods 2017
208
100

Single-Cell Transcriptomics of the Human Endocrine Pancreas.
Yue J Wang, Jonathan Schug, Kyoung-Jae Won, Chengyang Liu, Ali Naji, Dana Avrahami, Maria L Golson, Klaus H Kaestner. Diabetes 2016
171
100

pcaReduce: hierarchical clustering of single cell transcriptional profiles.
Justina Žurauskienė, Christopher Yau. BMC Bioinformatics 2016
106
100

Brain structure. Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq.
Amit Zeisel, Ana B Muñoz-Manchado, Simone Codeluppi, Peter Lönnerberg, Gioele La Manno, Anna Juréus, Sueli Marques, Hermany Munguba, Liqun He, Christer Betsholtz,[...]. Science 2015
100

An interpretable framework for clustering single-cell RNA-Seq datasets.
Jesse M Zhang, Jue Fan, H Christina Fan, David Rosenfeld, David N Tse. BMC Bioinformatics 2018
18
100

Combined Single-Cell Functional and Gene Expression Analysis Resolves Heterogeneity within Stem Cell Populations.
Nicola K Wilson, David G Kent, Florian Buettner, Mona Shehata, Iain C Macaulay, Fernando J Calero-Nieto, Manuel Sánchez Castillo, Caroline A Oedekoven, Evangelia Diamanti, Reiner Schulte,[...]. Cell Stem Cell 2015
254
100


Co-cited is the co-citation frequency, indicating how many articles cite the article together with the query article. Similarity is the co-citation as percentage of the times cited of the query article or the article in the search results, whichever is the lowest. These numbers are calculated for the last 100 citations when articles are cited more than 100 times.