Evidence map›Paper›PMID 31465854›Full record

ArticleGenomics, proteomics & bioinformatics2019

C

Chen-Yu Zhu, Chi Zhou, Yun-Qin Chen, Ai-Zong Shen, Zong-Ming Guo, Zhao-Yi Yang, Xiang-Yun Ye, Shen Qu, Jia Wei, Qi Liu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Genomics, proteomics & bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Chen-Yu ZhuDepartment of Endocrinology & Metabolism, Shanghai Tenth People's Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China.
Chi ZhouDepartment of Endocrinology & Metabolism, Shanghai Tenth People's Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China.
Yun-Qin ChenR&D Information, Innovation Center China, AstraZeneca, Shanghai 201203, China.
Ai-Zong ShenDepartment of Pharmacy, The First Affiliated Hospital of University of Science and Technology of China, Hefei 230036, China.
Zong-Ming GuoR&D Information, Innovation Center China, AstraZeneca, Shanghai 201203, China.
Zhao-Yi YangDepartment of Pharmacy, The First Affiliated Hospital of University of Science and Technology of China, Hefei 230036, China.
Xiang-Yun YeShanghai Chest Hospital, Shanghai Jiaotong University, Shanghai 200240, China. Electronic address: 56485747@qq.com.
Shen QuDepartment of Endocrinology & Metabolism, Shanghai Tenth People's Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China. Electronic address: qushencn@tongji.edu.cn.
Jia WeiR&D Information, Innovation Center China, AstraZeneca, Shanghai 201203, China. Electronic address: Jenny.Wei@astrazeneca.com.
Qi LiuDepartment of Endocrinology & Metabolism, Shanghai Tenth People's Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China; Department of Ophthalmology, Ninghai First Hospital, Ninghai 315600, China. Electronic address: qiliu@tongji.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Next-generation sequencing has allowed identification of millions of somatic mutations in human cancer cells. A key challenge in interpreting cancer genomes is to distinguish drivers of cancer development among available genetic mutations. To address this issue, we present the first web-based application, consensus cancer driver gene caller (C

Indexed as

AlgorithmsConsensus SequenceNeoplasmsCluster AnalysisHumansInternetMachine LearningCancer driver genesConsensusData integrationSomatic mutationWeb server

Identifiers

PMID31465854
PMCPMC6818389

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.