Evidence map›Paper›PMID 31984130›Full record

ArticleF1000Research2019

Biobtree: A tool to search, map and visualize bioinformatics identifiers and special keywords.

Tamer Gur

Abstract read
In one paragraph

Article in F1000Research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

1 author.

Tamer GurEuropean Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SD Cambridge, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Due to their nature, bioinformatics datasets are often closely related to each other. For this reason, search, mapping and visualization of these relations are often performed manually or programmatically via identifiers or special keywords such as gene symbols. Although various tools exist for these situations, the growing volume of bioinformatics datasets, emerging new software tools and approaches motivates new solutions. To provide a new tool for these current cases, I present the Biobtree bioinformatics tool. Biobtree effectively fetches and indexes identifiers and special keywords with their related identifiers from supported datasets, optionally with user pre-defined datasets and provides a web interface, web services and direct B+ tree data structure based single uniform database output. Biobtree can handle billions of identifiers and runs via a single executable file with no installation and dependency required. It also aims to provide a relatively small codebase for easy maintenance, addition of new features and extension to larger datasets. Biobtree is available to download from GitHub.

Indexed as

Computational BiologyData VisualizationSoftwareTerminology as TopicDatabases, FactualGenesbioinformaticsidentifiersmappingsearchvisualization

Identifiers

PMID31984130
PMCPMC6964641

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.