Evidence map›Paper›PMID 38877144›Full record

ArticleCommunications biology2024

BrainTACO: an explorable multi-scale multi-modal brain transcriptomic and connectivity data resource.

Florian Ganglberger, Dominic Kargl, Markus Töpfer, Julien Hernandez-Lallement, Nathan Lawless, Francesc Fernandez-Albert, Wulf Haubensak, Katja Bühler

Abstract read
In one paragraph

Article in Communications biology, 2024. 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

8 authors.

Florian GanglbergerBiomedical Image Informatics, VRVis Research Center, Vienna, Austria.ORCID 0000-0003-2211-663X
Dominic Kargl *Department of Neuronal Cell Biology, Vienna Medical University, Vienna, Austria.
Markus Töpfer *Biomedical Image Informatics, VRVis Research Center, Vienna, Austria.
Julien Hernandez-LallementGlobal Computational Biology and Digital Sciences, Boehringer Ingelheim Pharma, Biberach an der Riss, Germany.
Nathan LawlessGlobal Computational Biology and Digital Sciences, Boehringer Ingelheim Pharma, Biberach an der Riss, Germany.ORCID 0000-0002-3120-1126
Francesc Fernandez-AlbertGlobal Computational Biology and Digital Sciences, Boehringer Ingelheim Pharma, Biberach an der Riss, Germany.
Wulf HaubensakDepartment of Neuronal Cell Biology, Vienna Medical University, Vienna, Austria.ORCID 0000-0002-2034-9184
Katja BühlerBiomedical Image Informatics, VRVis Research Center, Vienna, Austria. buehler@vrvis.at.ORCID 0000-0002-0362-7998

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Exploring the relationships between genes and brain circuitry can be accelerated by joint analysis of heterogeneous datasets from 3D imaging data, anatomical data, as well as brain networks at varying scales, resolutions, and modalities. Generating an integrated view, beyond the individual resources' original purpose, requires the fusion of these data to a common space, and a visualization that bridges the gap across scales. However, despite ever expanding datasets, few platforms for integration and exploration of this heterogeneous data exist. To this end, we present the BrainTACO (Brain Transcriptomic And Connectivity Data) resource, a selection of heterogeneous, and multi-scale neurobiological data spatially mapped onto a common, hierarchical reference space, combined via a holistic data integration scheme. To access BrainTACO, we extended BrainTrawler, a web-based visual analytics framework for spatial neurobiological data, with comparative visualizations of multiple resources. This enables gene expression dissection of brain networks with, to the best of our knowledge, an unprecedented coverage and allows for the identification of potential genetic drivers of connectivity in both mice and humans that may contribute to the discovery of dysconnectivity phenotypes. Hence, BrainTACO reduces the need for time-consuming manual data aggregation often required for computational analyses in script-based toolboxes, and supports neuroscientists by directly leveraging the data instead of preparing it.

Indexed as

BrainTranscriptomeAnimalsDatabases, GeneticHumansMice

Identifiers

PMID38877144
PMCPMC11178817

What Socratic 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 Socratic graph.