Cargando…
Using Machine Learning to Identify Biomarkers Affecting Fat Deposition in Pigs by Integrating Multisource Transcriptome Information
[Image: see text] Fat deposition in pigs is not only closely related to pig production efficiency and pork quality but also an ideal model for human obesity. Transcriptome sequencing is widely used to study fat deposition. However, due to small sample sizes, high false positive rates, and poor consi...
Autores principales: | Liu, Huatao, Xing, Kai, Jiang, Yifan, Liu, Yibing, Wang, Chuduan, Ding, Xiangdong |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2022
|
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9413214/ https://www.ncbi.nlm.nih.gov/pubmed/35953074 http://dx.doi.org/10.1021/acs.jafc.2c03339 |
Ejemplares similares
-
Identification of key genes affecting porcine fat deposition based on co-expression network analysis of weighted genes
por: Xing, Kai, et al.
Publicado: (2021) -
Identification of Long Non-Coding RNAs Involved in Porcine Fat Deposition Using Two High-Throughput Sequencing Methods
por: Liu, Yibing, et al.
Publicado: (2021) -
Integration of Transcriptome and Whole Genomic Resequencing Data to Identify Key Genes Affecting Swine Fat Deposition
por: Xing, Kai, et al.
Publicado: (2015) -
A Single-Step Genome Wide Association Study on Body Size Traits Using Imputation-Based Whole-Genome Sequence Data in Yorkshire Pigs
por: Liu, Huatao, et al.
Publicado: (2021) -
Comparative adipose transcriptome analysis digs out genes related to fat deposition in two pig breeds
por: Xing, Kai, et al.
Publicado: (2019)