Evidence map›Paper›PMID 32921303›Full record

ArticleBMC bioinformatics2020

ANDDigest: a new web-based module of ANDSystem for the search of knowledge in the scientific literature.

Timofey V Ivanisenko, Olga V Saik, Pavel S Demenkov, Nikita V Ivanisenko, Alexander N Savostianov, Vladimir A Ivanisenko

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 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Integrating omics databases for enhanced crop breeding.Journal of integrative bioinformatics · 2023
    Review
  4. Article
  5. Research Topics of the Bioinformatics of Gene Regulation.International journal of molecular sciences · 2023
    Article
  6. BioGraph: Data Model for Linking and Querying Diverse Biological Metadata.International journal of molecular sciences · 2023
    Article
  7. Article
  8. Article
  9. Article
  10. Plant Biology and Biotechnology: Focus on Genomics and Bioinformatics.International journal of molecular sciences · 2022
    Article
  11. Article
  12. Article
  13. Bioinformatics research at SBB-2019.BMC bioinformatics · 2020
    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.

Timofey V IvanisenkoLaboratory of Computer-Assisted Proteomics, Institute of Cytology & Genetics, Siberian Branch, Russian Academy of Sciences, Prospekt Lavrentyeva 10, Novosibirsk, 630090, Russia. itv@bionet.nsc.ru.ORCID http://orcid.org/0000-0002-0005-9155
Olga V SaikLaboratory of Computer-Assisted Proteomics, Institute of Cytology & Genetics, Siberian Branch, Russian Academy of Sciences, Prospekt Lavrentyeva 10, Novosibirsk, 630090, Russia.
Pavel S DemenkovLaboratory of Computer-Assisted Proteomics, Institute of Cytology & Genetics, Siberian Branch, Russian Academy of Sciences, Prospekt Lavrentyeva 10, Novosibirsk, 630090, Russia.
Nikita V IvanisenkoLaboratory of Computer-Assisted Proteomics, Institute of Cytology & Genetics, Siberian Branch, Russian Academy of Sciences, Prospekt Lavrentyeva 10, Novosibirsk, 630090, Russia.
Alexander N SavostianovNovosibirsk State University, st. Pirogova 1, Novosibirsk, 630090, Russia.
Vladimir A IvanisenkoLaboratory of Computer-Assisted Proteomics, Institute of Cytology & Genetics, Siberian Branch, Russian Academy of Sciences, Prospekt Lavrentyeva 10, Novosibirsk, 630090, Russia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe rapid growth of scientific literature has rendered the task of finding relevant information one of the critical problems in almost any research. Search engines, like Google Scholar, Web of Knowledge, PubMed, Scopus, and others, are highly effective in document search; however, they do not allow knowledge extraction. In contrast to the search engines, text-mining systems provide extraction of knowledge with representations in the form of semantic networks. Of particular interest are tools performing a full cycle of knowledge management and engineering, including automated retrieval, integration, and representation of knowledge in the form of semantic networks, their visualization, and analysis. STRING, Pathway Studio, MetaCore, and others are well-known examples of such products. Previously, we developed the Associative Network Discovery System (ANDSystem), which also implements such a cycle. However, the drawback of these systems is dependence on the employed ontologies describing the subject area, which limits their functionality in searching information based on user-specified queries.

resultsThe ANDDigest system is a new web-based module of the ANDSystem tool, permitting searching within PubMed by using dictionaries from the ANDSystem tool and sets of user-defined keywords. ANDDigest allows performing the search based on complex queries simultaneously, taking into account many types of objects from the ANDSystem's ontology. The system has a user-friendly interface, providing sorting, visualization, and filtering of the found information, including mapping of mentioned objects in text, linking to external databases, sorting of data by publication date, citations number, journal H-indices, etc. The system provides data on trends for identified entities based on dynamics of interest according to the frequency of their mentions in PubMed by years.

conclusionsThe main feature of ANDDigest is its functionality, serving as a specialized search for information about multiple associative relationships of objects from the ANDSystem's ontology vocabularies, taking into account user-specified keywords. The tool can be applied to the interpretation of experimental genetics data, the search for associations between molecular genetics objects, and the preparation of scientific and analytical reviews. It is presently available at https://anddigest.sysbio.ru/ .

Indexed as

InternetSoftwareDatabases, FactualData MiningPubMedAssociative gene networkDynamics of interestInformation searchKnowledge retrievalText-miningTrend analysisWeb-based tool

Identifiers

PMID32921303
PMCPMC7488989

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.