A citation-based method for searching scientific literature


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



Times Cited
  Times     Co-cited
Similarity


Supervised risk predictor of breast cancer based on intrinsic subtypes.
Joel S Parker, Michael Mullins, Maggie C U Cheang, Samuel Leung, David Voduc, Tammi Vickery, Sherri Davies, Christiane Fauron, Xiaping He, Zhiyuan Hu,[...]. J Clin Oncol 2009
66

Network-based machine learning in colorectal and bladder organoid models predicts anti-cancer drug efficacy in patients.
JungHo Kong, Heetak Lee, Donghyo Kim, Seong Kyu Han, Doyeon Ha, Kunyoo Shin, Sanguk Kim. Nat Commun 2020
19
66


ComBat-seq: batch effect adjustment for RNA-seq count data.
Yuqing Zhang, Giovanni Parmigiani, W Evan Johnson. NAR Genom Bioinform 2020
43
33

A meta-learning approach for genomic survival analysis.
Yeping Lina Qiu, Hong Zheng, Arnout Devos, Heather Selby, Olivier Gevaert. Nat Commun 2020
8
33


Absolute assignment of breast cancer intrinsic molecular subtype.
Eric R Paquet, Michael T Hallett. J Natl Cancer Inst 2014
80
33

Differential Interleukin-2 Transcription Kinetics Render Mouse but Not Human T Cells Vulnerable to Splicing Inhibition Early after Activation.
Debojit Bose, Alexander Neumann, Bernd Timmermann, Stefan Meinke, Florian Heyd. Mol Cell Biol 2019
5
33

BERMUDA: a novel deep transfer learning method for single-cell RNA sequencing batch correction reveals hidden high-resolution cellular subtypes.
Tongxin Wang, Travis S Johnson, Wei Shao, Zixiao Lu, Bryan R Helm, Jie Zhang, Kun Huang. Genome Biol 2019
35
33

Global computational alignment of tumor and cell line transcriptional profiles.
Allison Warren, Yejia Chen, Andrew Jones, Tsukasa Shibue, William C Hahn, Jesse S Boehm, Francisca Vazquez, Aviad Tsherniak, James M McFarland. Nat Commun 2021
14
33


Pathway-based subnetworks enable cross-disease biomarker discovery.
Syed Haider, Cindy Q Yao, Vicky S Sabine, Michal Grzadkowski, Vincent Stimper, Maud H W Starmans, Jianxin Wang, Francis Nguyen, Nathalie C Moon, Xihui Lin,[...]. Nat Commun 2018
16
33

Deep-learning approach to identifying cancer subtypes using high-dimensional genomic data.
Runpu Chen, Le Yang, Steve Goodison, Yijun Sun. Bioinformatics 2020
19
33

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
33

Setting the standards for machine learning in biology.
David T Jones. Nat Rev Mol Cell Biol 2019
20
33

Deep learning-based cancer survival prognosis from RNA-seq data: approaches and evaluations.
Zhi Huang, Travis S Johnson, Zhi Han, Bryan Helm, Sha Cao, Chi Zhang, Paul Salama, Maher Rizkalla, Christina Y Yu, Jun Cheng,[...]. BMC Med Genomics 2020
16
33

Genetic Redundancy, Functional Compensation, and Cancer Vulnerability.
Matteo Cereda, Thanos P Mourikis, Francesca D Ciccarelli. Trends Cancer 2016
10
33

Standard machine learning approaches outperform deep representation learning on phenotype prediction from transcriptomics data.
Aaron M Smith, Jonathan R Walsh, John Long, Craig B Davis, Peter Henstock, Martin R Hodge, Mateusz Maciejewski, Xinmeng Jasmine Mu, Stephen Ra, Shanrong Zhao,[...]. BMC Bioinformatics 2020
12
33

A Machine Learning Approach for Identifying Gene Biomarkers Guiding the Treatment of Breast Cancer.
Ashraf Abou Tabl, Abedalrhman Alkhateeb, Waguih ElMaraghy, Luis Rueda, Alioune Ngom. Front Genet 2019
18
33


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
149
33

Identification and Analysis of Glioblastoma Biomarkers Based on Single Cell Sequencing.
Quan Cheng, Jing Li, Fan Fan, Hui Cao, Zi-Yu Dai, Ze-Yu Wang, Song-Shan Feng. Front Bioeng Biotechnol 2020
14
33


Identification of altered biological processes in heterogeneous RNA-sequencing data by discretization of expression profiles.
Andrea Lauria, Serena Peirone, Marco Del Giudice, Francesca Priante, Prabhakar Rajan, Michele Caselle, Salvatore Oliviero, Matteo Cereda. Nucleic Acids Res 2020
2
50

Machine learning for RNA sequencing-based intrinsic subtyping of breast cancer.
Silvia Cascianelli, Ivan Molineris, Claudio Isella, Marco Masseroli, Enzo Medico. Sci Rep 2020
9
33

Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles.
Aravind Subramanian, Pablo Tamayo, Vamsi K Mootha, Sayan Mukherjee, Benjamin L Ebert, Michael A Gillette, Amanda Paulovich, Scott L Pomeroy, Todd R Golub, Eric S Lander,[...]. Proc Natl Acad Sci U S A 2005
33

SMNN: batch effect correction for single-cell RNA-seq data via supervised mutual nearest neighbor detection.
Yuchen Yang, Gang Li, Huijun Qian, Kirk C Wilhelmsen, Yin Shen, Yun Li. Brief Bioinform 2021
7
33

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
33

Comprehensive Analysis of Alternative Splicing Across Tumors from 8,705 Patients.
André Kahles, Kjong-Van Lehmann, Nora C Toussaint, Matthias Hüser, Stefan G Stark, Timo Sachsenberg, Oliver Stegle, Oliver Kohlbacher, Chris Sander, Gunnar Rätsch. Cancer Cell 2018
262
33

xCell: digitally portraying the tissue cellular heterogeneity landscape.
Dvir Aran, Zicheng Hu, Atul J Butte. Genome Biol 2017
720
33

A 15-gene signature for prediction of colon cancer recurrence and prognosis based on SVM.
Guangru Xu, Minghui Zhang, Hongxing Zhu, Jinhua Xu. Gene 2017
52
33

Feature selection may improve deep neural networks for the bioinformatics problems.
Zheng Chen, Meng Pang, Zixin Zhao, Shuainan Li, Rui Miao, Yifan Zhang, Xiaoyue Feng, Xin Feng, Yexian Zhang, Meiyu Duan,[...]. Bioinformatics 2020
19
33

CUP-AI-Dx: A tool for inferring cancer tissue of origin and molecular subtype using RNA gene-expression data and artificial intelligence.
Yue Zhao, Ziwei Pan, Sandeep Namburi, Andrew Pattison, Atara Posner, Shiva Balachander, Carolyn A Paisie, Honey V Reddi, Jens Rueter, Anthony J Gill,[...]. EBioMedicine 2020
8
33

Unifying cancer and normal RNA sequencing data from different sources.
Qingguo Wang, Joshua Armenia, Chao Zhang, Alexander V Penson, Ed Reznik, Liguo Zhang, Thais Minet, Angelica Ochoa, Benjamin E Gross, Christine A Iacobuzio-Donahue,[...]. Sci Data 2018
51
33

Transfer learning with convolutional neural networks for cancer survival prediction using gene-expression data.
Guillermo López-García, José M Jerez, Leonardo Franco, Francisco J Veredas. PLoS One 2020
10
33

Maximizing the Utility of Cancer Transcriptomic Data.
Yu Xiang, Youqiong Ye, Zhao Zhang, Leng Han. Trends Cancer 2018
18
33

DeepSurv: personalized treatment recommender system using a Cox proportional hazards deep neural network.
Jared L Katzman, Uri Shaham, Alexander Cloninger, Jonathan Bates, Tingting Jiang, Yuval Kluger. BMC Med Res Methodol 2018
144
33


Determining cell type abundance and expression from bulk tissues with digital cytometry.
Aaron M Newman, Chloé B Steen, Chih Long Liu, Andrew J Gentles, Aadel A Chaudhuri, Florian Scherer, Michael S Khodadoust, Mohammad S Esfahani, Bogdan A Luca, David Steiner,[...]. Nat Biotechnol 2019
492
33

An overview of topic modeling and its current applications in bioinformatics.
Lin Liu, Lin Tang, Wen Dong, Shaowen Yao, Wei Zhou. Springerplus 2016
36
33


A Topic Modeling Analysis of TCGA Breast and Lung Cancer Transcriptomic Data.
Filippo Valle, Matteo Osella, Michele Caselle. Cancers (Basel) 2020
2
50

Pathway-based classification of glioblastoma uncovers a mitochondrial subtype with therapeutic vulnerabilities.
Luciano Garofano, Simona Migliozzi, Young Taek Oh, Fulvio D'Angelo, Ryan D Najac, Aram Ko, Brulinda Frangaj, Francesca Pia Caruso, Kai Yu, Jinzhou Yuan,[...]. Nat Cancer 2021
28
33

Computational and analytical challenges in single-cell transcriptomics.
Oliver Stegle, Sarah A Teichmann, John C Marioni. Nat Rev Genet 2015
548
33

Integrated analysis of single-cell RNA-seq and bulk RNA-seq unravels tumour heterogeneity plus M2-like tumour-associated macrophage infiltration and aggressiveness in TNBC.
Xuanwen Bao, Run Shi, Tianyu Zhao, Yanfang Wang, Natasa Anastasov, Michael Rosemann, Weijia Fang. Cancer Immunol Immunother 2021
17
33

Patients with genetically heterogeneous synchronous colorectal cancer carry rare damaging germline mutations in immune-related genes.
Matteo Cereda, Gennaro Gambardella, Lorena Benedetti, Fabio Iannelli, Dominic Patel, Gianluca Basso, Rosalinda F Guerra, Thanos P Mourikis, Ignazio Puccio, Shruti Sinha,[...]. Nat Commun 2016
29
33

Sequential analysis of transcript expression patterns improves survival prediction in multiple cancers.
Jordan Mandel, Raghunandan Avula, Edward V Prochownik. BMC Cancer 2020
3
33

Pooled Clustering of High-Grade Serous Ovarian Cancer Gene Expression Leads to Novel Consensus Subtypes Associated with Survival and Surgical Outcomes.
Chen Wang, Sebastian M Armasu, Kimberly R Kalli, Matthew J Maurer, Ethan P Heinzen, Gary L Keeney, William A Cliby, Ann L Oberg, Scott H Kaufmann, Ellen L Goode. Clin Cancer Res 2017
50
33

Mechanistic models versus machine learning, a fight worth fighting for the biological community?
Ruth E Baker, Jose-Maria Peña, Jayaratnam Jayamohan, Antoine Jérusalem. Biol Lett 2018
48
33

A Review of Matched-pairs Feature Selection Methods for Gene Expression Data Analysis.
Sen Liang, Anjun Ma, Sen Yang, Yan Wang, Qin Ma. Comput Struct Biotechnol J 2018
10
33


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.