Evidence map›Paper›PMID 42581402›Full record

ArticleJournal of integrative bioinformatics2026

Pithos - a scalable and secure data container for FAIR-compliant research data management in life sciences.

Jannis Schlegel, Sebastian Beyvers, Maria Hansen, Lukas Brehm, Alexander Goesmann, Frank Förster

Abstract read
In one paragraph

Article in Journal of integrative bioinformatics, 2026. 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

6 authors.

Jannis SchlegelBioinformatics and Systems Biology, Justus Liebig University Giessen, 35390, Giessen, Germany.ORCID https://orcid.org/0009-0004-4382-4760
Sebastian BeyversBioinformatics and Systems Biology, Justus Liebig University Giessen, 35390, Giessen, Germany.ORCID https://orcid.org/0000-0002-9747-7096
Maria HansenBioinformatics and Systems Biology, Justus Liebig University Giessen, 35390, Giessen, Germany.ORCID https://orcid.org/0009-0001-3265-8654
Lukas BrehmBioinformatics and Systems Biology, Justus Liebig University Giessen, 35390, Giessen, Germany.ORCID https://orcid.org/0009-0008-0887-0015
Alexander GoesmannBioinformatics and Systems Biology, Justus Liebig University Giessen, 35390, Giessen, Germany.ORCID https://orcid.org/0000-0002-7086-2568
Frank FörsterBioinformatics and Systems Biology, Justus Liebig University Giessen, 35390, Giessen, Germany.ORCID https://orcid.org/0000-0003-4166-5423

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Modern research techniques have led to exponential growth in the volume and complexity of scientific data. Consequently, managing these volumes securely and efficiently has become a major challenge. While all research domains face these challenges, life science research is particularly affected because current approaches often rely on a large set of different file formats, with metadata stored in separated databases or spreadsheets. This leads to fragmented datasets, orphaned data, and compromised research reproducibility. Traditional solutions also force researchers to choose between security and accessibility, with encrypted files preventing selective access and indexed formats lacking adequate security for sensitive data. These limitations are particularly problematic in large-scale genomic studies where researchers must decompress multi-gigabyte files to access specific regions, creating computational bottlenecks and inefficient network usage when working with cloud-stored datasets. We introduce Pithos, a next-generation file format specifically designed for scientific data management in distributed cloud environments. The format uses content-defined chunking to enable efficient deduplication across distributed storage systems, thereby reducing storage costs and bandwidth requirements. The append-only structure ensures data immutability and allows for incremental updates without compromising content. Benchmark results show that Pithos outperforms existing solutions in read and write performance, with comparable or improved storage efficiency.

Indexed as

Biological Science DisciplinesCloud ComputingComputer SecurityDatabase Management SystemsData ManagementSoftwareDatabases, FactualInformation Storage and Retrievaldata containerdata protectionintegrative bioinformaticsPithosresearch data management

Identifiers

PMID42581402
PMCPMC13526446

What OpenQuestion holds

Textmetadata
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.