Evidence map›Paper›PMID 39840283›Full record

ReviewFrontiers in genetics2024

Recent advances in deep learning and language models for studying the microbiome.

Binghao Yan, Yunbi Nam, Lingyao Li, Rebecca A Deek, Hongzhe Li, Siyuan Ma

Abstract readReview
In one paragraph

Review in Frontiers in genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
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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.

Binghao Yan *Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
Yunbi Nam *Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, United States.
Lingyao LiSchool of Information, University of South Florida, Tampa, FL, United States.
Rebecca A DeekDepartment of Biostatistics and Health Data Science, University of Pittsburgh, Pittsburgh, PA, United States.
Hongzhe LiDepartment of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
Siyuan MaDepartment of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, United States.

Funding

ECHO Laboratory Core at Vanderbilt for Integrated Sample Biobanking and ProcessingU24OD035523 · OD · VANDERBILT UNIVERSITY MEDICAL CENTER · PI Suman Ranjan Das, NATASHA Bassam HALASA · 2023 to 2026
$32.8M
Statistical Methods for Microbiome and MetagenomicsR01GM123056 · NIGMS · UNIVERSITY OF PENNSYLVANIA · PI LEE, HONGZHE · 2017 to 2025
$3.7M
NIGMS NIH HHS R01 GM123056NIH HHS U24 OD035523
6 · The paper itself

Abstract

Recent advancements in deep learning, particularly large language models (LLMs), made a significant impact on how researchers study microbiome and metagenomics data. Microbial protein and genomic sequences, like natural languages, form a

Indexed as

artificial intelligenceattentionlarge language modelsmicrobiometransformervirome

Identifiers

PMID39840283
PMCPMC11747409

What OpenQuestion holds

Textmetadata
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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.