Evidence map›Paper›PMID 40166164›Full record

ArticlebioRxiv : the preprint server for biology2025

AI-assisted isolation of bioactive Dipyrimicins from

Christine Mae F Ancajas, Isra E Shuster, Allison S Walker

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. 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.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Christine Mae F AncajasDepartment of Chemistry, Vanderbilt University, 1234 Stevenson Center Lane, Nashville, TN 37240, United States.ORCID 0000-0001-5697-2202
Isra E ShusterDepartment of Chemistry, Vanderbilt University, 1234 Stevenson Center Lane, Nashville, TN 37240, United States.ORCID 0009-0007-8746-8747
Allison S WalkerDepartment of Chemistry, Vanderbilt University, 1234 Stevenson Center Lane, Nashville, TN 37240, United States.ORCID 0000-0001-5666-7232

Funding

Machine learning approaches for the discovery, repurposing, and optimization of natural products with therapeutic potential - Supplement to support grad training of Adrian RussR35GM146987 · NIGMS · VANDERBILT UNIVERSITY · PI Allison Sara Walker · 2022 to 2026
$2.4M
NIGMS NIH HHS R35 GM146987
6 · The paper itself

Abstract

One of the major challenges in natural product discovery is the prioritization of compounds with useful activities from microbial sources. In particular, this is a challenge in genome mining for novel natural products, where the structures and activities of compounds produced by bioinformatically identified and uncharacterized biosynthetic gene clusters remain unknown. Here, we utilize a machine learning model to predict the antibacterial activity of a natural product from its biosynthetic gene cluster (BGC). We prioritized the strain

Identifiers

PMID40166164
PMCPMC11957118

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.