Evidence map›Paper›PMID 33371868›Full record

ArticleBMC bioinformatics2020

Accelerating bioinformatics research with International Conference on Intelligent Biology and Medicine 2020.

Yan Guo, Li Shen, Xinghua Shi, Kai Wang, Yulin Dai, Zhongming Zhao

Abstract read
In one paragraph

Article in BMC bioinformatics, 2020. 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. Applying the digital data and the bioinformatics tools in SARS-CoV-2 research.Computational and structural biotechnology journal · 2023
    Review
  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

6 authors.

Yan GuoDepartment of Internal Medicine, Comprehensive Cancer Center, University of New Mexico, Albuquerque, NM, 87131, USA. yaguo@salud.unm.edu.
Li ShenDepartment of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
Xinghua ShiDepartment of Computer and Information Sciences, College of Science and Technology, Temple University, Philadelphia, PA, 19122, USA.
Kai WangRaymond G. Perelman Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
Yulin DaiCenter for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA.
Zhongming ZhaoCenter for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA. zhongming.zhao@uth.tmc.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The International Association for Intelligent Biology and Medicine (IAIBM) is a nonprofit organization that promotes intelligent biology and medical science. It hosts an annual International Conference on Intelligent Biology and Medicine (ICIBM), which was initially established in 2012. Due to the coronavirus (COVID-19) pandemic, the ICIBM 2020 was held for the first time as a virtual online conference on August 9 to 10. The virtual conference had ~ 300 registered participants and featured 41 online real-time presentations. ICIBM 2020 received a total of 75 manuscript submissions, and 12 were selected to be published in this special issue of BMC Bioinformatics. These 12 manuscripts cover a wide range of bioinformatics topics including network analysis, imaging analysis, machine learning, gene expression analysis, and sequence analysis.

Indexed as

Congresses as TopicInternationalityMedicineResearchComputational BiologyCOVID-19Gene Expression RegulationGene Regulatory NetworksHumansMachine LearningSARS-CoV-2Sequence AnalysisGene expressionImagingMachine learningNetwork

Identifiers

PMID33371868
PMCPMC7767910

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.