Evidence map›Paper›PMID 41726874›Full record

ArticlebioRxiv : the preprint server for biology2026

Enhancing ML-based binder design with high-throughput screening: a comparison of mRNA and yeast display technologies.

Zhiyuan Yao, McGuire Metts, Avery K Huber, Jingjing Li, Tomoaki Kinjo, Henry Dieckhaus, Amrita Nallathambi, Albert A Bowers, Brian Kuhlman

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. 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

9 authors.

Zhiyuan YaoDepartment of Pharmacology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA.
McGuire MettsDepartment of Biochemistry and Biophysics, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA.ORCID 0009-0002-3847-8061
Avery K HuberDivision of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.ORCID 0000-0002-7824-0421
Jingjing LiDivision of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Tomoaki KinjoDepartment of Biochemistry and Biophysics, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA.ORCID 0000-0003-0939-7756
Henry DieckhausDepartment of Biochemistry and Biophysics, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA.ORCID 0000-0003-1390-2444
Amrita NallathambiDepartment of Biochemistry and Biophysics, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA.ORCID 0000-0001-5066-9528
Albert A BowersDivision of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.ORCID 0000-0001-8214-7484
Brian KuhlmanDepartment of Biochemistry and Biophysics, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA.ORCID 0000-0003-4907-9699

Funding

GPU workstation for deep learning-based protein design and cryo-EM data processingR35GM131923 · NIGMS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BRIAN A KUHLMAN · 2019 to 2026
$6.1M
MIRA Equipment SupplementR35GM125005 · NIGMS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Albert A Bowers · 2017 to 2026
$3.9M
NIGMS NIH HHS R35 GM125005NIGMS NIH HHS R35 GM131923
6 · The paper itself

Abstract

Recent advances in machine learning (ML)-based protein design methods have enabled the rapid

Identifiers

PMID41726874
PMCPMC12919099

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.