Evidence map›Paper›PMID 41535974›Full record

ArticleGenome biology2026

FSBLUP: a novel strategy of fusion similarity matrix construction via optimally integrating intermediate omics data to enhance genomic prediction.

Yahui Xue, Lei Zhou, Yue Zhuo, Weining Li, Sijia Ma, Heng Du, Wanying Li, Jicai Jiang, Jian-Feng Liu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Genome biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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

9 authors.

Yahui XueState Key Laboratory of Animal Biotech Breeding, Frontiers Science Center for Molecular Design Breeding (MOE), College of Animal Science and Technology, China Agricultural University, No.2 Yuanmingyuan West Road, Beijing, 100193, China.
Lei ZhouState Key Laboratory of Animal Biotech Breeding, Frontiers Science Center for Molecular Design Breeding (MOE), College of Animal Science and Technology, China Agricultural University, No.2 Yuanmingyuan West Road, Beijing, 100193, China.
Yue ZhuoState Key Laboratory of Animal Biotech Breeding, Frontiers Science Center for Molecular Design Breeding (MOE), College of Animal Science and Technology, China Agricultural University, No.2 Yuanmingyuan West Road, Beijing, 100193, China.
Weining LiInstitute of Animal Science, Jiangsu Academy of Agricultural Sciences, Nanjing, 210014, Jiangsu, China.
Sijia MaState Key Laboratory of Animal Biotech Breeding, Frontiers Science Center for Molecular Design Breeding (MOE), College of Animal Science and Technology, China Agricultural University, No.2 Yuanmingyuan West Road, Beijing, 100193, China.
Heng DuState Key Laboratory of Animal Biotech Breeding, Frontiers Science Center for Molecular Design Breeding (MOE), College of Animal Science and Technology, China Agricultural University, No.2 Yuanmingyuan West Road, Beijing, 100193, China.
Wanying LiState Key Laboratory of Animal Biotech Breeding, Frontiers Science Center for Molecular Design Breeding (MOE), College of Animal Science and Technology, China Agricultural University, No.2 Yuanmingyuan West Road, Beijing, 100193, China.
Jicai JiangDepartment of Animal Science, North Carolina State University, Raleigh, NC, 27695, USA.
Jian-Feng LiuState Key Laboratory of Animal Biotech Breeding, Frontiers Science Center for Molecular Design Breeding (MOE), College of Animal Science and Technology, China Agricultural University, No.2 Yuanmingyuan West Road, Beijing, 100193, China. liujf@cau.edu.cn.

Funding

Biological Breeding-Major Projects in National Science and Technology 2023ZD0404405Chinese Universities Scientific Fund 2023TC196Earmarked Fund for China Agriculture Research System CARS-pig-35National Natural Science Foundations of China 32272844National Natural Science Foundations of China 32302708Science and Technology Program of Guizhou Province Qian Kehe Support (2022) Key 032Seed Industry Vitalization Program of Guangdong Province 2022-440222-4301030201-0019
6 · The paper itself

Abstract

The increasing availability of multi-omics data is promising in enhancing genomic prediction in breeding and human genetics. However, integrating multi-omics data into genomic prediction models remains challenging due to complex relationships between omics layers and phenotypic outcomes. We propose Fusion Similarity Best Linear Unbiased Prediction (FSBLUP), a novel strategy that integrates genomic and intermediate omics data using a unified similarity matrix approach. FSBLUP systematically estimates how different omics layers contribute to phenotypic variation via machine-learning-optimized parameters that capture underlying genetic architecture of complex traits. FSBLUP demonstrates greater predictive accuracy than existing methods, as validated through theoretical and practical evaluations.

Indexed as

GenomicsHumansMachine LearningMultiomicsPhenotypePrediction AlgorithmsFusion similarity matrixGenomic predictionIntermediate omicsMachine learningMulti-omicsPhenomicsTranscriptomics

Identifiers

PMID41535974
PMCPMC12888590

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.