HelPredictor models single-cell transcriptome to predict human embryo lineage allocation.

Liang, Pengfei; Zheng, Lei; Long, Chunshen; Yang, Wuritu; Yang, Lei; Zuo, Yongchun

Liang, Pengfei; Zheng, Lei; Long, Chunshen; Yang, Wuritu; Yang, Lei; Zuo, Yongchun.

Affiliation

Liang P; State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, College of life Sciences, Inner Mongolia University, Hohhot 010070, China.
Zheng L; State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, College of Life Sciences, Inner Mongolia University, Hohhot 010070, China.
Long C; State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, College of Life Sciences, Inner Mongolia University, Hohhot 010070, China.
Yang W; State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, College of Life Sciences, Inner Mongolia University, Hohhot 010070, China.
Yang L; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Zuo Y; State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, College of Life Sciences, Inner Mongolia University, Hohhot 010070, China.

Brief Bioinform ; 22(6)2021 11 05.

Article in En | MEDLINE | ID: mdl-34037706

Subject(s)

Cell Lineage/genetics; Computational Biology/methods; Embryonic Development/genetics; Gene Expression Profiling/methods; Single-Cell Analysis/methods; Software; Transcriptome; Algorithms; Gene Expression Regulation, Developmental; Humans; Machine Learning; Reproducibility of Results; Workflow

Key words

cell identity; feature selection; lineage allocation; machine learning; single-cell RNA sequencing

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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Software / Cell Lineage / Computational Biology / Gene Expression Profiling / Embryonic Development / Single-Cell Analysis / Transcriptome Type of study: Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: Brief Bioinform Journal subject: BIOLOGIA / INFORMATICA MEDICA Year: 2021 Type: Article Affiliation country: China

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