A citation-based method for searching scientific literature

Devin C Koestler, Meaghan J Jones, Joseph Usset, Brock C Christensen, Rondi A Butler, Michael S Kobor, John K Wiencke, Karl T Kelsey. BMC Bioinformatics 2016
Times Cited: 66







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



Times Cited
  Times     Co-cited
Similarity


DNA methylation arrays as surrogate measures of cell mixture distribution.
Eugene Andres Houseman, William P Accomando, Devin C Koestler, Brock C Christensen, Carmen J Marsit, Heather H Nelson, John K Wiencke, Karl T Kelsey. BMC Bioinformatics 2012
81

Minfi: a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays.
Martin J Aryee, Andrew E Jaffe, Hector Corrada-Bravo, Christine Ladd-Acosta, Andrew P Feinberg, Kasper D Hansen, Rafael A Irizarry. Bioinformatics 2014
48

Differential DNA methylation in purified human blood cells: implications for cell lineage and studies on disease susceptibility.
Lovisa E Reinius, Nathalie Acevedo, Maaike Joerink, Göran Pershagen, Sven-Erik Dahlén, Dario Greco, Cilla Söderhäll, Annika Scheynius, Juha Kere. PLoS One 2012
655
42

An optimized library for reference-based deconvolution of whole-blood biospecimens assayed using the Illumina HumanMethylationEPIC BeadArray.
Lucas A Salas, Devin C Koestler, Rondi A Butler, Helen M Hansen, John K Wiencke, Karl T Kelsey, Brock C Christensen. Genome Biol 2018
97
34


Epigenome-wide association data implicate DNA methylation as an intermediary of genetic risk in rheumatoid arthritis.
Yun Liu, Martin J Aryee, Leonid Padyukov, M Daniele Fallin, Espen Hesselberg, Arni Runarsson, Lovisa Reinius, Nathalie Acevedo, Margaret Taub, Marcus Ronninger,[...]. Nat Biotechnol 2013
599
31

Genome-wide methylation profiles reveal quantitative views of human aging rates.
Gregory Hannum, Justin Guinney, Ling Zhao, Li Zhang, Guy Hughes, SriniVas Sadda, Brandy Klotzle, Marina Bibikova, Jian-Bing Fan, Yuan Gao,[...]. Mol Cell 2013
25

Quantitative reconstruction of leukocyte subsets using DNA methylation.
William P Accomando, John K Wiencke, E Andres Houseman, Heather H Nelson, Karl T Kelsey. Genome Biol 2014
95
24

A comparison of reference-based algorithms for correcting cell-type heterogeneity in Epigenome-Wide Association Studies.
Andrew E Teschendorff, Charles E Breeze, Shijie C Zheng, Stephan Beck. BMC Bioinformatics 2017
133
24


Reference-free cell mixture adjustments in analysis of DNA methylation data.
Eugene Andres Houseman, John Molitor, Carmen J Marsit. Bioinformatics 2014
274
19

DNA methylation of cord blood cell types: Applications for mixed cell birth studies.
Kelly M Bakulski, Jason I Feinberg, Shan V Andrews, Jack Yang, Shannon Brown, Stephanie L McKenney, Frank Witter, Jeremy Walston, Andrew P Feinberg, M Daniele Fallin. Epigenetics 2016
176
19

Sparse PCA corrects for cell type heterogeneity in epigenome-wide association studies.
Elior Rahmani, Noah Zaitlen, Yael Baran, Celeste Eng, Donglei Hu, Joshua Galanter, Sam Oh, Esteban G Burchard, Eleazar Eskin, James Zou,[...]. Nat Methods 2016
120
19

Robust enumeration of cell subsets from tissue expression profiles.
Aaron M Newman, Chih Long Liu, Michael R Green, Andrew J Gentles, Weiguo Feng, Yue Xu, Chuong D Hoang, Maximilian Diehn, Ash A Alizadeh. Nat Methods 2015
18

Reference-free deconvolution of DNA methylation data and mediation by cell composition effects.
E Andres Houseman, Molly L Kile, David C Christiani, Tan A Ince, Karl T Kelsey, Carmen J Marsit. BMC Bioinformatics 2016
118
18


Cell-type deconvolution from DNA methylation: a review of recent applications.
Alexander J Titus, Rachel M Gallimore, Lucas A Salas, Brock C Christensen. Hum Mol Genet 2017
68
18

Adjusting batch effects in microarray expression data using empirical Bayes methods.
W Evan Johnson, Cheng Li, Ariel Rabinovic. Biostatistics 2007
16


DNA Methylation-Derived Neutrophil-to-Lymphocyte Ratio: An Epigenetic Tool to Explore Cancer Inflammation and Outcomes.
Devin C Koestler, Joseph Usset, Brock C Christensen, Carmen J Marsit, Margaret R Karagas, Karl T Kelsey, John K Wiencke. Cancer Epidemiol Biomarkers Prev 2017
42
26

Epigenome-wide association studies without the need for cell-type composition.
James Zou, Christoph Lippert, David Heckerman, Martin Aryee, Jennifer Listgarten. Nat Methods 2014
134
16


Discovery of cross-reactive probes and polymorphic CpGs in the Illumina Infinium HumanMethylation450 microarray.
Yi-an Chen, Mathieu Lemire, Sanaa Choufani, Darci T Butcher, Daria Grafodatskaya, Brent W Zanke, Steven Gallinger, Thomas J Hudson, Rosanna Weksberg. Epigenetics 2013
877
15

Cell type specific DNA methylation in cord blood: A 450K-reference data set and cell count-based validation of estimated cell type composition.
Kristina Gervin, Christian Magnus Page, Hans Christian D Aass, Michelle A Jansen, Heidi Elisabeth Fjeldstad, Bettina Kulle Andreassen, Liesbeth Duijts, Joyce B van Meurs, Menno C van Zelm, Vincent W Jaddoe,[...]. Epigenetics 2016
45
22

Immunomethylomic approach to explore the blood neutrophil lymphocyte ratio (NLR) in glioma survival.
John K Wiencke, Devin C Koestler, Lucas A Salas, Joseph L Wiemels, Ritu P Roy, Helen M Hansen, Terri Rice, Lucie S McCoy, Paige M Bracci, Annette M Molinaro,[...]. Clin Epigenetics 2017
38
26

Integrative analysis of 111 reference human epigenomes.
Anshul Kundaje, Wouter Meuleman, Jason Ernst, Misha Bilenky, Angela Yen, Alireza Heravi-Moussavi, Pouya Kheradpour, Zhizhuo Zhang, Jianrong Wang, Michael J Ziller,[...]. Nature 2015
13

limma powers differential expression analyses for RNA-sequencing and microarray studies.
Matthew E Ritchie, Belinda Phipson, Di Wu, Yifang Hu, Charity W Law, Wei Shi, Gordon K Smyth. Nucleic Acids Res 2015
13

Blood-based profiles of DNA methylation predict the underlying distribution of cell types: a validation analysis.
Devin C Koestler, Brock Christensen, Margaret R Karagas, Carmen J Marsit, Scott M Langevin, Karl T Kelsey, John K Wiencke, E Andres Houseman. Epigenetics 2013
158
13

A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450 k DNA methylation data.
Andrew E Teschendorff, Francesco Marabita, Matthias Lechner, Thomas Bartlett, Jesper Tegner, David Gomez-Cabrero, Stephan Beck. Bioinformatics 2013
813
13

The sva package for removing batch effects and other unwanted variation in high-throughput experiments.
Jeffrey T Leek, W Evan Johnson, Hilary S Parker, Andrew E Jaffe, John D Storey. Bioinformatics 2012
12

DNA methylation outliers in normal breast tissue identify field defects that are enriched in cancer.
Andrew E Teschendorff, Yang Gao, Allison Jones, Matthias Ruebner, Matthias W Beckmann, David L Wachter, Peter A Fasching, Martin Widschwendter. Nat Commun 2016
117
12


An evaluation of methods correcting for cell-type heterogeneity in DNA methylation studies.
Kevin McGregor, Sasha Bernatsky, Ines Colmegna, Marie Hudson, Tomi Pastinen, Aurélie Labbe, Celia M T Greenwood. Genome Biol 2016
91
12

missMethyl: an R package for analyzing data from Illumina's HumanMethylation450 platform.
Belinda Phipson, Jovana Maksimovic, Alicia Oshlack. Bioinformatics 2016
291
12

High density DNA methylation array with single CpG site resolution.
Marina Bibikova, Bret Barnes, Chan Tsan, Vincent Ho, Brandy Klotzle, Jennie M Le, David Delano, Lu Zhang, Gary P Schroth, Kevin L Gunderson,[...]. Genomics 2011
10

Epigenome-wide association studies for common human diseases.
Vardhman K Rakyan, Thomas A Down, David J Balding, Stephan Beck. Nat Rev Genet 2011
775
10

Correlation of an epigenetic mitotic clock with cancer risk.
Zhen Yang, Andrew Wong, Diana Kuh, Dirk S Paul, Vardhman K Rakyan, R David Leslie, Shijie C Zheng, Martin Widschwendter, Stephan Beck, Andrew E Teschendorff. Genome Biol 2016
97
10

Cell-composition effects in the analysis of DNA methylation array data: a mathematical perspective.
E Andres Houseman, Karl T Kelsey, John K Wiencke, Carmen J Marsit. BMC Bioinformatics 2015
55
12

Using control genes to correct for unwanted variation in microarray data.
Johann A Gagnon-Bartsch, Terence P Speed. Biostatistics 2012
226
10

Associating cellular epigenetic models with human phenotypes.
Tuuli Lappalainen, John M Greally. Nat Rev Genet 2017
145
10

Identification of differentially methylated cell types in epigenome-wide association studies.
Shijie C Zheng, Charles E Breeze, Stephan Beck, Andrew E Teschendorff. Nat Methods 2018
66
10

Systematic evaluation and validation of reference and library selection methods for deconvolution of cord blood DNA methylation data.
Kristina Gervin, Lucas A Salas, Kelly M Bakulski, Menno C van Zelm, Devin C Koestler, John K Wiencke, Liesbeth Duijts, Henriëtte A Moll, Karl T Kelsey, Michael S Kobor,[...]. Clin Epigenetics 2019
41
17

Estimation of blood cellular heterogeneity in newborns and children for epigenome-wide association studies.
Paul Yousefi, Karen Huen, Hong Quach, Girish Motwani, Alan Hubbard, Brenda Eskenazi, Nina Holland. Environ Mol Mutagen 2015
35
17


Comparison of Beta-value and M-value methods for quantifying methylation levels by microarray analysis.
Pan Du, Xiao Zhang, Chiang-Ching Huang, Nadereh Jafari, Warren A Kibbe, Lifang Hou, Simon M Lin. BMC Bioinformatics 2010
9


DNA Methylation in Whole Blood: Uses and Challenges.
E Andres Houseman, Stephanie Kim, Karl T Kelsey, John K Wiencke. Curr Environ Health Rep 2015
81
9

Prognostic role of neutrophil-to-lymphocyte ratio in solid tumors: a systematic review and meta-analysis.
Arnoud J Templeton, Mairéad G McNamara, Boštjan Šeruga, Francisco E Vera-Badillo, Priya Aneja, Alberto Ocaña, Raya Leibowitz-Amit, Guru Sonpavde, Jennifer J Knox, Ben Tran,[...]. J Natl Cancer Inst 2014
9

Epigenetic Signatures of Cigarette Smoking.
Roby Joehanes, Allan C Just, Riccardo E Marioni, Luke C Pilling, Lindsay M Reynolds, Pooja R Mandaviya, Weihua Guan, Tao Xu, Cathy E Elks, Stella Aslibekyan,[...]. Circ Cardiovasc Genet 2016
394
9



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.