A citation-based method for searching scientific literature

Romain Lopez, Jeffrey Regier, Michael B Cole, Michael I Jordan, Nir Yosef. Nat Methods 2018
Times Cited: 227







List of co-cited articles
712 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
43

Single-cell RNA-seq denoising using a deep count autoencoder.
Gökcen Eraslan, Lukas M Simon, Maria Mircea, Nikola S Mueller, Fabian J Theis. Nat Commun 2019
174
41

Batch effects in single-cell RNA-sequencing data are corrected by matching mutual nearest neighbors.
Laleh Haghverdi, Aaron T L Lun, Michael D Morgan, John C Marioni. Nat Biotechnol 2018
474
35

Integrating single-cell transcriptomic data across different conditions, technologies, and species.
Andrew Butler, Paul Hoffman, Peter Smibert, Efthymia Papalexi, Rahul Satija. Nat Biotechnol 2018
34

Massively parallel digital transcriptional profiling of single cells.
Grace X Y Zheng, Jessica M Terry, Phillip Belgrader, Paul Ryvkin, Zachary W Bent, Ryan Wilson, Solongo B Ziraldo, Tobias D Wheeler, Geoff P McDermott, Junjie Zhu,[...]. Nat Commun 2017
32

SCANPY: large-scale single-cell gene expression data analysis.
F Alexander Wolf, Philipp Angerer, Fabian J Theis. Genome Biol 2018
720
30

Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets.
Evan Z Macosko, Anindita Basu, Rahul Satija, James Nemesh, Karthik Shekhar, Melissa Goldman, Itay Tirosh, Allison R Bialas, Nolan Kamitaki, Emily M Martersteck,[...]. Cell 2015
30

Fast, sensitive and accurate integration of single-cell data with Harmony.
Ilya Korsunsky, Nghia Millard, Jean Fan, Kamil Slowikowski, Fan Zhang, Kevin Wei, Yuriy Baglaenko, Michael Brenner, Po-Ru Loh, Soumya Raychaudhuri. Nat Methods 2019
400
29

Single-Cell Multi-omic Integration Compares and Contrasts Features of Brain Cell Identity.
Joshua D Welch, Velina Kozareva, Ashley Ferreira, Charles Vanderburg, Carly Martin, Evan Z Macosko. Cell 2019
215
24

Challenges in unsupervised clustering of single-cell RNA-seq data.
Vladimir Yu Kiselev, Tallulah S Andrews, Martin Hemberg. Nat Rev Genet 2019
215
22

scmap: projection of single-cell RNA-seq data across data sets.
Vladimir Yu Kiselev, Andrew Yiu, Martin Hemberg. Nat Methods 2018
179
22

Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells.
Allon M Klein, Linas Mazutis, Ilke Akartuna, Naren Tallapragada, Adrian Veres, Victor Li, Leonid Peshkin, David A Weitz, Marc W Kirschner. Cell 2015
22

Current best practices in single-cell RNA-seq analysis: a tutorial.
Malte D Luecken, Fabian J Theis. Mol Syst Biol 2019
308
21

Efficient integration of heterogeneous single-cell transcriptomes using Scanorama.
Brian Hie, Bryan Bryson, Bonnie Berger. Nat Biotechnol 2019
123
21

Recovering Gene Interactions from Single-Cell Data Using Data Diffusion.
David van Dijk, Roshan Sharma, Juozas Nainys, Kristina Yim, Pooja Kathail, Ambrose J Carr, Cassandra Burdziak, Kevin R Moon, Christine L Chaffer, Diwakar Pattabiraman,[...]. Cell 2018
352
20

The Human Cell Atlas.
Aviv Regev, Sarah A Teichmann, Eric S Lander, Ido Amit, Christophe Benoist, Ewan Birney, Bernd Bodenmiller, Peter Campbell, Piero Carninci, Menna Clatworthy,[...]. Elife 2017
668
20

Spatial reconstruction of single-cell gene expression data.
Rahul Satija, Jeffrey A Farrell, David Gennert, Alexander F Schier, Aviv Regev. Nat Biotechnol 2015
20

Splatter: simulation of single-cell RNA sequencing data.
Luke Zappia, Belinda Phipson, Alicia Oshlack. Genome Biol 2017
184
19


Dimensionality reduction for visualizing single-cell data using UMAP.
Etienne Becht, Leland McInnes, John Healy, Charles-Antoine Dutertre, Immanuel W H Kwok, Lai Guan Ng, Florent Ginhoux, Evan W Newell. Nat Biotechnol 2018
821
19

Bayesian approach to single-cell differential expression analysis.
Peter V Kharchenko, Lev Silberstein, David T Scadden. Nat Methods 2014
543
18

Simultaneous epitope and transcriptome measurement in single cells.
Marlon Stoeckius, Christoph Hafemeister, William Stephenson, Brian Houck-Loomis, Pratip K Chattopadhyay, Harold Swerdlow, Rahul Satija, Peter Smibert. Nat Methods 2017
673
18

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
17

A general and flexible method for signal extraction from single-cell RNA-seq data.
Davide Risso, Fanny Perraudeau, Svetlana Gribkova, Sandrine Dudoit, Jean-Philippe Vert. Nat Commun 2018
180
17

SAVER: gene expression recovery for single-cell RNA sequencing.
Mo Huang, Jingshu Wang, Eduardo Torre, Hannah Dueck, Sydney Shaffer, Roberto Bonasio, John I Murray, Arjun Raj, Mingyao Li, Nancy R Zhang. Nat Methods 2018
176
17


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
462
17

The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells.
Cole Trapnell, Davide Cacchiarelli, Jonna Grimsby, Prapti Pokharel, Shuqiang Li, Michael Morse, Niall J Lennon, Kenneth J Livak, Tarjei S Mikkelsen, John L Rinn. Nat Biotechnol 2014
17

A Single-Cell Transcriptome Atlas of the Human Pancreas.
Mauro J Muraro, Gitanjali Dharmadhikari, Dominic Grün, Nathalie Groen, Tim Dielen, Erik Jansen, Leon van Gurp, Marten A Engelse, Francoise Carlotti, Eelco J P de Koning,[...]. Cell Syst 2016
373
16

Mapping the Mouse Cell Atlas by Microwell-Seq.
Xiaoping Han, Renying Wang, Yincong Zhou, Lijiang Fei, Huiyu Sun, Shujing Lai, Assieh Saadatpour, Ziming Zhou, Haide Chen, Fang Ye,[...]. Cell 2018
402
16

Eleven grand challenges in single-cell data science.
David Lähnemann, Johannes Köster, Ewa Szczurek, Davis J McCarthy, Stephanie C Hicks, Mark D Robinson, Catalina A Vallejos, Kieran R Campbell, Niko Beerenwinkel, Ahmed Mahfouz,[...]. Genome Biol 2020
142
15

From Louvain to Leiden: guaranteeing well-connected communities.
V A Traag, L Waltman, N J van Eck. Sci Rep 2019
259
15

Exploring single-cell data with deep multitasking neural networks.
Matthew Amodio, David van Dijk, Krishnan Srinivasan, William S Chen, Hussein Mohsen, Kevin R Moon, Allison Campbell, Yujiao Zhao, Xiaomei Wang, Manjunatha Venkataswamy,[...]. Nat Methods 2019
56
26

A comparison of automatic cell identification methods for single-cell RNA sequencing data.
Tamim Abdelaal, Lieke Michielsen, Davy Cats, Dylan Hoogduin, Hailiang Mei, Marcel J T Reinders, Ahmed Mahfouz. Genome Biol 2019
90
15


Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2.
Michael I Love, Wolfgang Huber, Simon Anders. Genome Biol 2014
14

A benchmark of batch-effect correction methods for single-cell RNA sequencing data.
Hoa Thi Nhu Tran, Kok Siong Ang, Marion Chevrier, Xiaomeng Zhang, Nicole Yee Shin Lee, Michelle Goh, Jinmiao Chen. Genome Biol 2020
127
14

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
400
14

A comparison of single-cell trajectory inference methods.
Wouter Saelens, Robrecht Cannoodt, Helena Todorov, Yvan Saeys. Nat Biotechnol 2019
292
13

Droplet scRNA-seq is not zero-inflated.
Valentine Svensson. Nat Biotechnol 2020
53
24

Generalizing RNA velocity to transient cell states through dynamical modeling.
Volker Bergen, Marius Lange, Stefan Peidli, F Alexander Wolf, Fabian J Theis. Nat Biotechnol 2020
171
13

Data denoising with transfer learning in single-cell transcriptomics.
Jingshu Wang, Divyansh Agarwal, Mo Huang, Gang Hu, Zilu Zhou, Chengzhong Ye, Nancy R Zhang. Nat Methods 2019
40
30

Computational and analytical challenges in single-cell transcriptomics.
Oliver Stegle, Sarah A Teichmann, John C Marioni. Nat Rev Genet 2015
533
12

Data-Driven Phenotypic Dissection of AML Reveals Progenitor-like Cells that Correlate with Prognosis.
Jacob H Levine, Erin F Simonds, Sean C Bendall, Kara L Davis, El-ad D Amir, Michelle D Tadmor, Oren Litvin, Harris G Fienberg, Astraea Jager, Eli R Zunder,[...]. Cell 2015
678
12

The single-cell transcriptional landscape of mammalian organogenesis.
Junyue Cao, Malte Spielmann, Xiaojie Qiu, Xingfan Huang, Daniel M Ibrahim, Andrew J Hill, Fan Zhang, Stefan Mundlos, Lena Christiansen, Frank J Steemers,[...]. Nature 2019
444
12

RNA velocity of single cells.
Gioele La Manno, Ruslan Soldatov, Amit Zeisel, Emelie Braun, Hannah Hochgerner, Viktor Petukhov, Katja Lidschreiber, Maria E Kastriti, Peter Lönnerberg, Alessandro Furlan,[...]. Nature 2018
676
12

Visualization and analysis of gene expression in tissue sections by spatial transcriptomics.
Patrik L Ståhl, Fredrik Salmén, Sanja Vickovic, Anna Lundmark, José Fernández Navarro, Jens Magnusson, Stefania Giacomello, Michaela Asp, Jakub O Westholm, Mikael Huss,[...]. Science 2016
576
12

Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution.
Samuel G Rodriques, Robert R Stickels, Aleksandrina Goeva, Carly A Martin, Evan Murray, Charles R Vanderburg, Joshua Welch, Linlin M Chen, Fei Chen, Evan Z Macosko. Science 2019
402
12

Systematic comparison of single-cell and single-nucleus RNA-sequencing methods.
Jiarui Ding, Xian Adiconis, Sean K Simmons, Monika S Kowalczyk, Cynthia C Hession, Nemanja D Marjanovic, Travis K Hughes, Marc H Wadsworth, Tyler Burks, Lan T Nguyen,[...]. Nat Biotechnol 2020
123
12

Deep learning enables accurate clustering with batch effect removal in single-cell RNA-seq analysis.
Xiangjie Li, Kui Wang, Yafei Lyu, Huize Pan, Jingxiao Zhang, Dwight Stambolian, Katalin Susztak, Muredach P Reilly, Gang Hu, Mingyao Li. Nat Commun 2020
29
41


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.