Evidence map›Paper›PMID 40386440›Full record

ArticleSynthetic and systems biotechnology2025

Sequence and taxonomic feature evaluation facilitated the discovery of alcohol oxidases.

Yilei Han, Xuwei Ding, Junjian Tan, Yajuan Sun, Yunjiang Duan, Zheng Liu, Gaowei Zheng, Diannan Lu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Synthetic and systems biotechnology, 2025. 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.

Yilei HanDepartment of Chemical Engineering, Tsinghua University, Beijing, 100084, China.
Xuwei DingState Key Laboratory of Bioreactor Engineering, Shanghai Collaborative Innovation Center for Biomanufacturing, East China University of Science and Technology, Shanghai, 200237, China.
Junjian TanDepartment of Chemical Engineering, Tsinghua University, Beijing, 100084, China.
Yajuan SunState Key Laboratory of Bioreactor Engineering, Shanghai Collaborative Innovation Center for Biomanufacturing, East China University of Science and Technology, Shanghai, 200237, China.
Yunjiang DuanDepartment of Chemical Engineering, Tsinghua University, Beijing, 100084, China.
Zheng LiuDepartment of Chemical Engineering, Tsinghua University, Beijing, 100084, China.
Gaowei ZhengState Key Laboratory of Bioreactor Engineering, Shanghai Collaborative Innovation Center for Biomanufacturing, East China University of Science and Technology, Shanghai, 200237, China.
Diannan LuDepartment of Chemical Engineering, Tsinghua University, Beijing, 100084, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent advancements in data technology offer immense opportunities for the discovery and development of new enzymes for the green synthesis of chemicals. Current protein databases predominantly prioritize overall sequence matches. The multi-scale features underpinning catalytic mechanisms and processes, which are scattered across various data sources, have not been sufficiently integrated to be effectively utilized in enzyme mining. In this study, we developed a sequence- and taxonomic-feature evaluation driven workflow to discover enzymes that can be expressed in

Indexed as

alcohol oxidaseEnzyme discoveryMachine learningsequence similiarty network

Identifiers

PMID40386440
PMCPMC12083922

What Socratic 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 Socratic graph.