Evidence map›Paper›PMID 37566630›Full record

ArticleDatabase : the journal of biological databases and curation2023

CCIDB: a manually curated cell-cell interaction database with cell context information.

Jin Young Noh, Hae In Lee, Ji-Hye Choi, Seong-Ho Cho, Yoon Hui Yi, Ji Hyun Lim, Eun Been Myung, Ye Ju Shin, Hyo Jin Shin, Hyun Goo Woo

Abstract read
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Article in Database : the journal of biological databases and curation, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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.

Jin Young NohDepartment of Physiology, Ajou University School of Medicine, Suwon 16499, Republic of Korea.
Hae In LeeDepartment of Physiology, Ajou University School of Medicine, Suwon 16499, Republic of Korea.
Ji-Hye ChoiDepartment of Physiology, Ajou University School of Medicine, Suwon 16499, Republic of Korea.
Seong-Ho ChoDepartment of Physiology, Ajou University School of Medicine, Suwon 16499, Republic of Korea.
Yoon Hui YiAjou University Data Center for Biomedicine & Pharmacotherapeutics (AUDC-BMPT), Ajou University School of Medicine, Suwon 16499, Republic of Korea.
Ji Hyun LimAjou University Data Center for Biomedicine & Pharmacotherapeutics (AUDC-BMPT), Ajou University School of Medicine, Suwon 16499, Republic of Korea.
Eun Been MyungAjou University Data Center for Biomedicine & Pharmacotherapeutics (AUDC-BMPT), Ajou University School of Medicine, Suwon 16499, Republic of Korea.
Ye Ju ShinAjou University Data Center for Biomedicine & Pharmacotherapeutics (AUDC-BMPT), Ajou University School of Medicine, Suwon 16499, Republic of Korea.
Hyo Jin ShinAjou University Data Center for Biomedicine & Pharmacotherapeutics (AUDC-BMPT), Ajou University School of Medicine, Suwon 16499, Republic of Korea.
Hyun Goo WooDepartment of Physiology, Ajou University School of Medicine, Suwon 16499, Republic of Korea.ORCID 0000-0002-0916-893X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cell-cell interaction (CCI) is a crucial event in the development and function of multicellular organisms. The development of CCI databases is beneficial for researchers who want to analyze single-cell sequencing data or study CCI through molecular experiments. CCIs are known to act differently according to cellular and biological contexts such as cell types, gene mutations or disease status; however, previous CCI databases do not completely provide this contextual information pertaining to CCIs. We constructed a cell-cell interaction database (CCIDB) containing the biological and clinical contexts involved in each interaction. To build a database of cellular and tissue contexts, we collected 38 types of context features, which were categorized into seven categories, including 'interaction', 'cell type', 'cofactor', 'effector', 'phenotype', 'pathology' and 'reference'. CCIs were manually retrieved from 272 studies published recently (less than 6 years ago). In the current version of CCIDB, 520 CCIs and their 38 context features have been manually collected and curated by biodata engineers. We suggest that CCIDB is a manually curated CCI resource that is highly useful, especially for analyzing context-dependent alterations in CCIs. Database URL https://ccidb.sysmed.kr/.

Indexed as

Cell CommunicationDatabases, Factual

Identifiers

PMID37566630
PMCPMC10419333

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Registered trials

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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.