A citation-based method for searching scientific literature

Gökcen Eraslan, Lukas M Simon, Maria Mircea, Nikola S Mueller, Fabian J Theis. Nat Commun 2019
Times Cited: 236







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



Times Cited
  Times     Co-cited
Similarity


Deep generative modeling for single-cell transcriptomics.
Romain Lopez, Jeffrey Regier, Michael B Cole, Michael I Jordan, Nir Yosef. Nat Methods 2018
325
58

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
227
40

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
454
38


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
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
28

Integrating single-cell transcriptomic data across different conditions, technologies, and species.
Andrew Butler, Paul Hoffman, Peter Smibert, Efthymia Papalexi, Rahul Satija. Nat Biotechnol 2018
27

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
26

Bayesian approach to single-cell differential expression analysis.
Peter V Kharchenko, Lev Silberstein, David T Scadden. Nat Methods 2014
600
23

Spatial reconstruction of single-cell gene expression data.
Rahul Satija, Jeffrey A Farrell, David Gennert, Alexander F Schier, Aviv Regev. Nat Biotechnol 2015
23

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

Splatter: simulation of single-cell RNA sequencing data.
Luke Zappia, Belinda Phipson, Alicia Oshlack. Genome Biol 2017
256
22

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
600
21

SCANPY: large-scale single-cell gene expression data analysis.
F Alexander Wolf, Philipp Angerer, Fabian J Theis. Genome Biol 2018
21

DeepImpute: an accurate, fast, and scalable deep neural network method to impute single-cell RNA-seq data.
Cédric Arisdakessian, Olivier Poirion, Breck Yunits, Xun Zhu, Lana X Garmire. Genome Biol 2019
69
30

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
20

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
76
25



AutoImpute: Autoencoder based imputation of single-cell RNA-seq data.
Divyanshu Talwar, Aanchal Mongia, Debarka Sengupta, Angshul Majumdar. Sci Rep 2018
53
33

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
545
17

Challenges in unsupervised clustering of single-cell RNA-seq data.
Vladimir Yu Kiselev, Tallulah S Andrews, Martin Hemberg. Nat Rev Genet 2019
281
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
227
17


DrImpute: imputing dropout events in single cell RNA sequencing data.
Wuming Gong, Il-Youp Kwak, Pruthvi Pota, Naoko Koyano-Nakagawa, Daniel J Garry. BMC Bioinformatics 2018
116
16

Scalable analysis of cell-type composition from single-cell transcriptomics using deep recurrent learning.
Yue Deng, Feng Bao, Qionghai Dai, Lani F Wu, Steven J Altschuler. Nat Methods 2019
55
29

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
485
15

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
15

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
14

Comparative Analysis of Single-Cell RNA Sequencing Methods.
Christoph Ziegenhain, Beate Vieth, Swati Parekh, Björn Reinius, Amy Guillaumet-Adkins, Martha Smets, Heinrich Leonhardt, Holger Heyn, Ines Hellmann, Wolfgang Enard. Mol Cell 2017
620
14

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

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
303
14

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
696
14

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
897
14

Current best practices in single-cell RNA-seq analysis: a tutorial.
Malte D Luecken, Fabian J Theis. Mol Syst Biol 2019
440
13

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
599
13



A comparison of single-cell trajectory inference methods.
Wouter Saelens, Robrecht Cannoodt, Helena Todorov, Yvan Saeys. Nat Biotechnol 2019
400
13

Slingshot: cell lineage and pseudotime inference for single-cell transcriptomics.
Kelly Street, Davide Risso, Russell B Fletcher, Diya Das, John Ngai, Nir Yosef, Elizabeth Purdom, Sandrine Dudoit. BMC Genomics 2018
481
12

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
827
12

scIGANs: single-cell RNA-seq imputation using generative adversarial networks.
Yungang Xu, Zhigang Zhang, Lei You, Jiajia Liu, Zhiwei Fan, Xiaobo Zhou. Nucleic Acids Res 2020
27
44

Computational and analytical challenges in single-cell transcriptomics.
Oliver Stegle, Sarah A Teichmann, John C Marioni. Nat Rev Genet 2015
579
12

Single-cell chromatin accessibility reveals principles of regulatory variation.
Jason D Buenrostro, Beijing Wu, Ulrike M Litzenburger, Dave Ruff, Michael L Gonzales, Michael P Snyder, Howard Y Chang, William J Greenleaf. Nature 2015
912
12

Joint profiling of chromatin accessibility and gene expression in thousands of single cells.
Junyue Cao, Darren A Cusanovich, Vijay Ramani, Delasa Aghamirzaie, Hannah A Pliner, Andrew J Hill, Riza M Daza, Jose L McFaline-Figueroa, Jonathan S Packer, Lena Christiansen,[...]. Science 2018
303
12

edgeR: a Bioconductor package for differential expression analysis of digital gene expression data.
Mark D Robinson, Davis J McCarthy, Gordon K Smyth. Bioinformatics 2010
11

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
938
11

Diffusion pseudotime robustly reconstructs lineage branching.
Laleh Haghverdi, Maren Büttner, F Alexander Wolf, Florian Buettner, Fabian J Theis. Nat Methods 2016
421
11

Reversed graph embedding resolves complex single-cell trajectories.
Xiaojie Qiu, Qi Mao, Ying Tang, Li Wang, Raghav Chawla, Hannah A Pliner, Cole Trapnell. Nat Methods 2017
11

mRNA-Seq whole-transcriptome analysis of a single cell.
Fuchou Tang, Catalin Barbacioru, Yangzhou Wang, Ellen Nordman, Clarence Lee, Nanlan Xu, Xiaohui Wang, John Bodeau, Brian B Tuch, Asim Siddiqui,[...]. Nat Methods 2009
11


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.