A citation-based method for searching scientific literature

Matthew Amodio, David van Dijk, Krishnan Srinivasan, William S Chen, Hussein Mohsen, Kevin R Moon, Allison Campbell, Yujiao Zhao, Xiaomei Wang, Manjunatha Venkataswamy, Anita Desai, V Ravi, Priti Kumar, Ruth Montgomery, Guy Wolf, Smita Krishnaswamy. Nat Methods 2019
Times Cited: 58







List of co-cited articles
380 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
252
58

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
189
51

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
29



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
27

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

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
190
25

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
24

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
52
26

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
380
24

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
43
30

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
186
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
511
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
20

AutoImpute: Autoencoder based imputation of single-cell RNA-seq data.
Divyanshu Talwar, Aanchal Mongia, Debarka Sengupta, Angshul Majumdar. Sci Rep 2018
39
30

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

scGen predicts single-cell perturbation responses.
Mohammad Lotfollahi, F Alexander Wolf, Fabian J Theis. Nat Methods 2019
37
29

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

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
454
17

Bayesian approach to single-cell differential expression analysis.
Peter V Kharchenko, Lev Silberstein, David T Scadden. Nat Methods 2014
553
17

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
712
17

SCANPY: large-scale single-cell gene expression data analysis.
F Alexander Wolf, Philipp Angerer, Fabian J Theis. Genome Biol 2018
812
17

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
739
17

scVAE: variational auto-encoders for single-cell gene expression data.
Christopher Heje Grønbech, Maximillian Fornitz Vording, Pascal N Timshel, Casper Kaae Sønderby, Tune H Pers, Ole Winther. Bioinformatics 2020
31
32

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
96
17


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
15


Splatter: simulation of single-cell RNA sequencing data.
Luke Zappia, Belinda Phipson, Alicia Oshlack. Genome Biol 2017
202
15

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
42
21

Validation of noise models for single-cell transcriptomics.
Dominic Grün, Lennart Kester, Alexander van Oudenaarden. Nat Methods 2014
334
13


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
710
13

Current best practices in single-cell RNA-seq analysis: a tutorial.
Malte D Luecken, Fabian J Theis. Mol Syst Biol 2019
346
13


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
918
12

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
12


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
433
12

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
553
12

Visualizing structure and transitions in high-dimensional biological data.
Kevin R Moon, David van Dijk, Zheng Wang, Scott Gigante, Daniel B Burkhardt, William S Chen, Kristina Yim, Antonia van den Elzen, Matthew J Hirn, Ronald R Coifman,[...]. Nat Biotechnol 2019
112
12

Droplet scRNA-seq is not zero-inflated.
Valentine Svensson. Nat Biotechnol 2020
56
12

Deep learning.
Yann LeCun, Yoshua Bengio, Geoffrey Hinton. Nature 2015
12

Using neural networks for reducing the dimensions of single-cell RNA-Seq data.
Chieh Lin, Siddhartha Jain, Hannah Kim, Ziv Bar-Joseph. Nucleic Acids Res 2017
77
10

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
10

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
732
10

A comparison of single-cell trajectory inference methods.
Wouter Saelens, Robrecht Cannoodt, Helena Todorov, Yvan Saeys. Nat Biotechnol 2019
319
10

Quantitative single-cell RNA-seq with unique molecular identifiers.
Saiful Islam, Amit Zeisel, Simon Joost, Gioele La Manno, Pawel Zajac, Maria Kasper, Peter Lönnerberg, Sten Linnarsson. Nat Methods 2014
608
10


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.