A citation-based method for searching scientific literature

Wenhao Tang, François Bertaux, Philipp Thomas, Claire Stefanelli, Malika Saint, Samuel Marguerat, Vahid Shahrezaei. Bioinformatics 2020
Times Cited: 16







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



Times Cited
  Times     Co-cited
Similarity


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
75


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
75

Deep generative modeling for single-cell transcriptomics.
Romain Lopez, Jeffrey Regier, Michael B Cole, Michael I Jordan, Nir Yosef. Nat Methods 2018
252
68

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
62

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
62

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
62

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
56

Missing data and technical variability in single-cell RNA-sequencing experiments.
Stephanie C Hicks, F William Townes, Mingxiang Teng, Rafael A Irizarry. Biostatistics 2018
149
50


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
43

Bayesian approach to single-cell differential expression analysis.
Peter V Kharchenko, Lev Silberstein, David T Scadden. Nat Methods 2014
553
37

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
37

MAST: a flexible statistical framework for assessing transcriptional changes and characterizing heterogeneity in single-cell RNA sequencing data.
Greg Finak, Andrew McDavid, Masanao Yajima, Jingyuan Deng, Vivian Gersuk, Alex K Shalek, Chloe K Slichter, Hannah W Miller, M Juliana McElrath, Martin Prlic,[...]. Genome Biol 2015
654
37

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
37


Pooling across cells to normalize single-cell RNA sequencing data with many zero counts.
Aaron T L Lun, Karsten Bach, John C Marioni. Genome Biol 2016
392
37

A systematic evaluation of single cell RNA-seq analysis pipelines.
Beate Vieth, Swati Parekh, Christoph Ziegenhain, Wolfgang Enard, Ines Hellmann. Nat Commun 2019
89
37

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
37

AutoImpute: Autoencoder based imputation of single-cell RNA-seq data.
Divyanshu Talwar, Aanchal Mongia, Debarka Sengupta, Angshul Majumdar. Sci Rep 2018
39
37


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
37

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
171
37

Power analysis of single-cell RNA-sequencing experiments.
Valentine Svensson, Kedar Nath Natarajan, Lam-Ha Ly, Ricardo J Miragaia, Charlotte Labalette, Iain C Macaulay, Ana Cvejic, Sarah A Teichmann. Nat Methods 2017
260
31

Feature selection and dimension reduction for single-cell RNA-Seq based on a multinomial model.
F William Townes, Stephanie C Hicks, Martin J Aryee, Rafael A Irizarry. Genome Biol 2019
71
31

SCANPY: large-scale single-cell gene expression data analysis.
F Alexander Wolf, Philipp Angerer, Fabian J Theis. Genome Biol 2018
812
31

Challenges in unsupervised clustering of single-cell RNA-seq data.
Vladimir Yu Kiselev, Tallulah S Andrews, Martin Hemberg. Nat Rev Genet 2019
234
31

A comparison of single-cell trajectory inference methods.
Wouter Saelens, Robrecht Cannoodt, Helena Todorov, Yvan Saeys. Nat Biotechnol 2019
319
31

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
440
31

Integrating single-cell transcriptomic data across different conditions, technologies, and species.
Andrew Butler, Paul Hoffman, Peter Smibert, Efthymia Papalexi, Rahul Satija. Nat Biotechnol 2018
31

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
31

Splatter: simulation of single-cell RNA sequencing data.
Luke Zappia, Belinda Phipson, Alicia Oshlack. Genome Biol 2017
202
31

Droplet scRNA-seq is not zero-inflated.
Valentine Svensson. Nat Biotechnol 2020
56
31

Current best practices in single-cell RNA-seq analysis: a tutorial.
Malte D Luecken, Fabian J Theis. Mol Syst Biol 2019
346
31

edgeR: a Bioconductor package for differential expression analysis of digital gene expression data.
Mark D Robinson, Davis J McCarthy, Gordon K Smyth. Bioinformatics 2010
25

A UNIFIED STATISTICAL FRAMEWORK FOR SINGLE CELL AND BULK RNA SEQUENCING DATA.
Lingxue Zhu, Jing Lei, Bernie Devlin, Kathryn Roeder. Ann Appl Stat 2018
28
25

powsimR: power analysis for bulk and single cell RNA-seq experiments.
Beate Vieth, Christoph Ziegenhain, Swati Parekh, Wolfgang Enard, Ines Hellmann. Bioinformatics 2017
52
25

Design and computational analysis of single-cell RNA-sequencing experiments.
Rhonda Bacher, Christina Kendziorski. Genome Biol 2016
210
25

Cicero Predicts cis-Regulatory DNA Interactions from Single-Cell Chromatin Accessibility Data.
Hannah A Pliner, Jonathan S Packer, José L McFaline-Figueroa, Darren A Cusanovich, Riza M Daza, Delasa Aghamirzaie, Sanjay Srivatsan, Xiaojie Qiu, Dana Jackson, Anna Minkina,[...]. Mol Cell 2018
150
25

False signals induced by single-cell imputation.
Tallulah S Andrews, Martin Hemberg. F1000Res 2018
47
25

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
25


Benchmarking single cell RNA-sequencing analysis pipelines using mixture control experiments.
Luyi Tian, Xueyi Dong, Saskia Freytag, Kim-Anh Lê Cao, Shian Su, Abolfazl JalalAbadi, Daniela Amann-Zalcenstein, Tom S Weber, Azadeh Seidi, Jafar S Jabbari,[...]. Nat Methods 2019
89
25

Computational and analytical challenges in single-cell transcriptomics.
Oliver Stegle, Sarah A Teichmann, John C Marioni. Nat Rev Genet 2015
548
25

Comparison of Computational Methods for Imputing Single-Cell RNA-Sequencing Data.
Lihua Zhang, Shihua Zhang. IEEE/ACM Trans Comput Biol Bioinform 2020
44
25

A systematic performance evaluation of clustering methods for single-cell RNA-seq data.
Angelo Duò, Mark D Robinson, Charlotte Soneson. F1000Res 2018
93
25

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
25

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
58
25

McImpute: Matrix Completion Based Imputation for Single Cell RNA-seq Data.
Aanchal Mongia, Debarka Sengupta, Angshul Majumdar. Front Genet 2019
17
25

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
25


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.