Evidence map›Paper›PMID 34900127›Full record

ArticleComputational and structural biotechnology journal2021

MIKB: A manually curated and comprehensive knowledge base for myocardial infarction.

Chaoying Zhan, Yingbo Zhang, Xingyun Liu, Rongrong Wu, Ke Zhang, Wenjing Shi, Li Shen, Ke Shen, Xuemeng Fan, Fei Ye and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Computational and structural biotechnology journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. PPCRKB: a risk factor knowledge base of postoperative pulmonary complications.Database : the journal of biological databases and curation · 2024
    Article
  3. Review
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

11 authors.

Chaoying ZhanInstitutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Sichuan 610212, China.
Yingbo ZhangInstitutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Sichuan 610212, China.
Xingyun LiuInstitutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Sichuan 610212, China.
Rongrong WuInstitutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Sichuan 610212, China.
Ke ZhangInstitutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Sichuan 610212, China.
Wenjing ShiInstitutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Sichuan 610212, China.
Li ShenInstitutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Sichuan 610212, China.
Ke ShenInstitutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Sichuan 610212, China.
Xuemeng FanInstitutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Sichuan 610212, China.
Fei YeInstitutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Sichuan 610212, China.
Bairong ShenInstitutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Sichuan 610212, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Myocardial infarction knowledge base (MIKB; http://www.sysbio.org.cn/mikb/; latest update: December 31, 2020) is an open-access and manually curated database dedicated to integrating knowledge about MI to improve the efficiency of translational MI research. MIKB is an updated and expanded version of our previous MI Risk Knowledge Base (MIRKB), which integrated MI-related risk factors and risk models for providing help in risk assessment or diagnostic prediction of MI. The updated MIRKB includes 9701 records with 2054 single factors, 209 combined factors, 243 risk models, 37 MI subtypes and 3406 interactions between single factors and MIs collected from 4817 research articles. The expanded functional module,

Indexed as

GeneticsKnowledge baseMulti-omicsMyocardial infarctionRisk factor

Identifiers

PMID34900127
PMCPMC8626632

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.