A citation-based method for searching scientific literature

Jinchen Li, Leisheng Shi, Kun Zhang, Yi Zhang, Shanshan Hu, Tingting Zhao, Huajing Teng, Xianfeng Li, Yi Jiang, Liying Ji, Zhongsheng Sun. Nucleic Acids Res 2018
Times Cited: 79







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



Times Cited
  Times     Co-cited
Similarity


ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data.
Kai Wang, Mingyao Li, Hakon Hakonarson. Nucleic Acids Res 2010
31

A method and server for predicting damaging missense mutations.
Ivan A Adzhubei, Steffen Schmidt, Leonid Peshkin, Vasily E Ramensky, Anna Gerasimova, Peer Bork, Alexey S Kondrashov, Shamil R Sunyaev. Nat Methods 2010
26

REVEL: An Ensemble Method for Predicting the Pathogenicity of Rare Missense Variants.
Nilah M Ioannidis, Joseph H Rothstein, Vikas Pejaver, Sumit Middha, Shannon K McDonnell, Saurabh Baheti, Anthony Musolf, Qing Li, Emily Holzinger, Danielle Karyadi,[...]. Am J Hum Genet 2016
556
22

Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology.
Sue Richards, Nazneen Aziz, Sherri Bale, David Bick, Soma Das, Julie Gastier-Foster, Wayne W Grody, Madhuri Hegde, Elaine Lyon, Elaine Spector,[...]. Genet Med 2015
22

A general framework for estimating the relative pathogenicity of human genetic variants.
Martin Kircher, Daniela M Witten, Preti Jain, Brian J O'Roak, Gregory M Cooper, Jay Shendure. Nat Genet 2014
20

Analysis of protein-coding genetic variation in 60,706 humans.
Monkol Lek, Konrad J Karczewski, Eric V Minikel, Kaitlin E Samocha, Eric Banks, Timothy Fennell, Anne H O'Donnell-Luria, James S Ware, Andrew J Hill, Beryl B Cummings,[...]. Nature 2016
20

Performance evaluation of pathogenicity-computation methods for missense variants.
Jinchen Li, Tingting Zhao, Yi Zhang, Kun Zhang, Leisheng Shi, Yun Chen, Xingxing Wang, Zhongsheng Sun. Nucleic Acids Res 2018
74
21

Predicting the functional impact of protein mutations: application to cancer genomics.
Boris Reva, Yevgeniy Antipin, Chris Sander. Nucleic Acids Res 2011
16

M-CAP eliminates a majority of variants of uncertain significance in clinical exomes at high sensitivity.
Karthik A Jagadeesh, Aaron M Wenger, Mark J Berger, Harendra Guturu, Peter D Stenson, David N Cooper, Jonathan A Bernstein, Gill Bejerano. Nat Genet 2016
352
16

An integrative approach to predicting the functional effects of non-coding and coding sequence variation.
Hashem A Shihab, Mark F Rogers, Julian Gough, Matthew Mort, David N Cooper, Ian N M Day, Tom R Gaunt, Colin Campbell. Bioinformatics 2015
278
16

DANN: a deep learning approach for annotating the pathogenicity of genetic variants.
Daniel Quang, Yifei Chen, Xiaohui Xie. Bioinformatics 2015
403
16

Comparison and integration of deleteriousness prediction methods for nonsynonymous SNVs in whole exome sequencing studies.
Chengliang Dong, Peng Wei, Xueqiu Jian, Richard Gibbs, Eric Boerwinkle, Kai Wang, Xiaoming Liu. Hum Mol Genet 2015
516
15

Predicting the functional effect of amino acid substitutions and indels.
Yongwook Choi, Gregory E Sims, Sean Murphy, Jason R Miller, Agnes P Chan. PLoS One 2012
15


Evolutionarily conserved elements in vertebrate, insect, worm, and yeast genomes.
Adam Siepel, Gill Bejerano, Jakob S Pedersen, Angie S Hinrichs, Minmei Hou, Kate Rosenbloom, Hiram Clawson, John Spieth, Ladeana W Hillier, Stephen Richards,[...]. Genome Res 2005
15

Identifying Mendelian disease genes with the variant effect scoring tool.
Hannah Carter, Christopher Douville, Peter D Stenson, David N Cooper, Rachel Karchin. BMC Genomics 2013
205
15

The contribution of de novo coding mutations to autism spectrum disorder.
Ivan Iossifov, Brian J O'Roak, Stephan J Sanders, Michael Ronemus, Niklas Krumm, Dan Levy, Holly A Stessman, Kali T Witherspoon, Laura Vives, Karynne E Patterson,[...]. Nature 2014
13

Predicting the functional, molecular, and phenotypic consequences of amino acid substitutions using hidden Markov models.
Hashem A Shihab, Julian Gough, David N Cooper, Peter D Stenson, Gary L A Barker, Keith J Edwards, Ian N M Day, Tom R Gaunt. Hum Mutat 2013
616
13

A spectral approach integrating functional genomic annotations for coding and noncoding variants.
Iuliana Ionita-Laza, Kenneth McCallum, Bin Xu, Joseph D Buxbaum. Nat Genet 2016
248
13

SIFT: Predicting amino acid changes that affect protein function.
Pauline C Ng, Steven Henikoff. Nucleic Acids Res 2003
13

Identifying novel constrained elements by exploiting biased substitution patterns.
Manuel Garber, Mitchell Guttman, Michele Clamp, Michael C Zody, Nir Friedman, Xiaohui Xie. Bioinformatics 2009
201
12

MutationTaster evaluates disease-causing potential of sequence alterations.
Jana Marie Schwarz, Christian Rödelsperger, Markus Schuelke, Dominik Seelow. Nat Methods 2010
12

Identifying a high fraction of the human genome to be under selective constraint using GERP++.
Eugene V Davydov, David L Goode, Marina Sirota, Gregory M Cooper, Arend Sidow, Serafim Batzoglou. PLoS Comput Biol 2010
890
12

A global reference for human genetic variation.
Adam Auton, Lisa D Brooks, Richard M Durbin, Erik P Garrison, Hyun Min Kang, Jan O Korbel, Jonathan L Marchini, Shane McCarthy, Gil A McVean, Gonçalo R Abecasis. Nature 2015
12

Genes with de novo mutations are shared by four neuropsychiatric disorders discovered from NPdenovo database.
Jinchen Li, Tao Cai, Yi Jiang, Huiqian Chen, Xin He, Chao Chen, Xianfeng Li, Qianzhi Shao, Xia Ran, Zhongshan Li,[...]. Mol Psychiatry 2016
92
11

COSMIC: somatic cancer genetics at high-resolution.
Simon A Forbes, David Beare, Harry Boutselakis, Sally Bamford, Nidhi Bindal, John Tate, Charlotte G Cole, Sari Ward, Elisabeth Dawson, Laura Ponting,[...]. Nucleic Acids Res 2017
11


Targeted sequencing and functional analysis reveal brain-size-related genes and their networks in autism spectrum disorders.
Jinchen Li, Lin Wang, Hui Guo, Leisheng Shi, Kun Zhang, Meina Tang, Shanshan Hu, Shanshan Dong, Yanling Liu, Tianyun Wang,[...]. Mol Psychiatry 2017
42
19

A statistical framework to predict functional non-coding regions in the human genome through integrated analysis of annotation data.
Qiongshi Lu, Yiming Hu, Jiehuan Sun, Yuwei Cheng, Kei-Hoi Cheung, Hongyu Zhao. Sci Rep 2015
75
10


ClinVar: public archive of interpretations of clinically relevant variants.
Melissa J Landrum, Jennifer M Lee, Mark Benson, Garth Brown, Chen Chao, Shanmuga Chitipiralla, Baoshan Gu, Jennifer Hart, Douglas Hoffman, Jeffrey Hoover,[...]. Nucleic Acids Res 2016
10

MutationTaster2: mutation prediction for the deep-sequencing age.
Jana Marie Schwarz, David N Cooper, Markus Schuelke, Dominik Seelow. Nat Methods 2014
10


Gene4Denovo: an integrated database and analytic platform for de novo mutations in humans.
Guihu Zhao, Kuokuo Li, Bin Li, Zheng Wang, Zhenghuan Fang, Xiaomeng Wang, Yi Zhang, Tengfei Luo, Qiao Zhou, Lin Wang,[...]. Nucleic Acids Res 2020
19
42

Synaptic, transcriptional and chromatin genes disrupted in autism.
Silvia De Rubeis, Xin He, Arthur P Goldberg, Christopher S Poultney, Kaitlin Samocha, A Erucment Cicek, Yan Kou, Li Liu, Menachem Fromer, Susan Walker,[...]. Nature 2014
8


Disruptive CHD8 mutations define a subtype of autism early in development.
Raphael Bernier, Christelle Golzio, Bo Xiong, Holly A Stessman, Bradley P Coe, Osnat Penn, Kali Witherspoon, Jennifer Gerdts, Carl Baker, Anneke T Vulto-van Silfhout,[...]. Cell 2014
400
7

Vitamin D-related genes are subjected to significant de novo mutation burdens in autism spectrum disorder.
Jinchen Li, Lin Wang, Ping Yu, Leisheng Shi, Kun Zhang, Zhong Sheng Sun, Kun Xia. Am J Med Genet B Neuropsychiatr Genet 2017
13
46

Whole genome sequencing resource identifies 18 new candidate genes for autism spectrum disorder.
Ryan K C Yuen, Daniele Merico, Matt Bookman, Jennifer L Howe, Bhooma Thiruvahindrapuram, Rohan V Patel, Joe Whitney, Nicole Deflaux, Jonathan Bingham, Zhuozhi Wang,[...]. Nat Neurosci 2017
355
7

International network of cancer genome projects.
Thomas J Hudson, Warwick Anderson, Axel Artez, Anna D Barker, Cindy Bell, Rosa R Bernabé, M K Bhan, Fabien Calvo, Iiro Eerola, Daniela S Gerhard,[...]. Nature 2010
7

Detection of nonneutral substitution rates on mammalian phylogenies.
Katherine S Pollard, Melissa J Hubisz, Kate R Rosenbloom, Adam Siepel. Genome Res 2010
7

The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data.
Aaron McKenna, Matthew Hanna, Eric Banks, Andrey Sivachenko, Kristian Cibulskis, Andrew Kernytsky, Kiran Garimella, David Altshuler, Stacey Gabriel, Mark Daly,[...]. Genome Res 2010
7

Predicting functional effect of human missense mutations using PolyPhen-2.
Ivan Adzhubei, Daniel M Jordan, Shamil R Sunyaev. Curr Protoc Hum Genet 2013
7

CADD: predicting the deleteriousness of variants throughout the human genome.
Philipp Rentzsch, Daniela Witten, Gregory M Cooper, Jay Shendure, Martin Kircher. Nucleic Acids Res 2019
909
7


Whole-genome sequencing in autism identifies hot spots for de novo germline mutation.
Jacob J Michaelson, Yujian Shi, Madhusudan Gujral, Hancheng Zheng, Dheeraj Malhotra, Xin Jin, Minghan Jian, Guangming Liu, Douglas Greer, Abhishek Bhandari,[...]. Cell 2012
334
6

De novo genic mutations among a Chinese autism spectrum disorder cohort.
Tianyun Wang, Hui Guo, Bo Xiong, Holly A F Stessman, Huidan Wu, Bradley P Coe, Tychele N Turner, Yanling Liu, Wenjing Zhao, Kendra Hoekzema,[...]. Nat Commun 2016
159
6

Integrated model of de novo and inherited genetic variants yields greater power to identify risk genes.
Xin He, Stephan J Sanders, Li Liu, Silvia De Rubeis, Elaine T Lim, James S Sutcliffe, Gerard D Schellenberg, Richard A Gibbs, Mark J Daly, Joseph D Buxbaum,[...]. PLoS Genet 2013
133
6

The evaluation of tools used to predict the impact of missense variants is hindered by two types of circularity.
Dominik G Grimm, Chloé-Agathe Azencott, Fabian Aicheler, Udo Gieraths, Daniel G MacArthur, Kaitlin E Samocha, David N Cooper, Peter D Stenson, Mark J Daly, Jordan W Smoller,[...]. Hum Mutat 2015
141
6



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.