Evidence map›Paper›PMID 38562853›Full record

ArticlebioRxiv : the preprint server for biology2024

PIPETS: A statistically informed, gene-annotation agnostic analysis method to study bacterial termination using 3'-end sequencing.

Quinlan Furumo, Michelle Meyer

Open access · greenAbstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Quinlan FurumoDepartment of Biology, Boston College, Chestnut Hill, MA, 02135, United States.
Michelle MeyerDepartment of Biology, Boston College, Chestnut Hill, MA, 02135, United States.ORCID 0000-0001-7014-9271
Boston College · US

Funding

Using Fitness Landscapes to assess RNA Structure-Function Relationships From Inside the CellR01GM134259 · NIGMS · BOSTON COLLEGE · PI MEYER, MICHELLE MARGARET · 2020 to 2023
$1.6M
Interactions between translation inhibiting antibiotics and diverse RNA regulatory mechanism in pathogenic bacteria affect drug sensitivityR21AI148895 · NIAID · BOSTON COLLEGE · PI MEYER, MICHELLE MARGARET, VAN OPIJNEN, TIM · 2020 to 2021
$430k
NIAID NIH HHS R21 AI148895NIGMS NIH HHS R01 GM134259
6 · The paper itself

Abstract

Background: Over the last decade the drop in short-read sequencing costs has allowed experimental techniques utilizing sequencing to address specific biological questions to proliferate, oVentimes outpacing standardized or effective analysis approaches for the data generated. There are growing amounts of bacterial 3'-end sequencing data, yet there is currently no commonly accepted analysis methodology for this datatype. Most data analysis approaches are somewhat Results: We present PIPETS, ( Conclusions: PIPETS provides a broadly applicable placorm to explore and analyze 3'-end sequencing data sets from across different organisms. It requires only the 3'-end sequencing data, and is broadly accessible to non-expert users.

Identifiers

PMID38562853
PMCPMC10983905
OpenAlexW4392973231

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.