Cell-type marker genes and functional enrichment analysis. by Hailin Li (453832)

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Spatial transcriptomics (ST) and single-cell atlases of multiple human tissues. by Huamei Li (8815955)

Assessment of multiple parameters for Cell2Spatial performance and assignment strategy. by Huamei Li (8815955)

Expression and functional analysis of MRGs. by Xuefen Lin (17785367)

Accuracy metrics of mapping tools on spatial transcriptomics (ST) data from multiple tissues. by Huamei Li (8815955)

Cell communication and establishment of senescence score. by Xihao Shen (20347942)

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Single-cell analysis of KTx rejection and healthy individuals. by Xihao Shen (20347942)

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Functional pathways and evaluation of mutation between the two MRG-related risk groups. by Xuefen Lin (17785367)

Possible LR interactions between endothelial cells and podocytes in DKD. by Hailin Li (453832)

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Transparent transfer function precomputed rendering diagram. by Yuliang Yuan (4478698)

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Skin transfer function ankle render diagram. by Yuliang Yuan (4478698)

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Bone transfer function pelvis render diagram. by Yuliang Yuan (4478698)

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Dimension reduction and cell annotation in scRNA-seq GSE131882. by Hailin Li (453832)

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Transparent transfer function precomputed rendering result diagram. by Yuliang Yuan (4478698)

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Functional enrichment and correlation analysis of hub DE-SRGs. by Xihao Shen (20347942)

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ProSAAS is expressed in multiple cell types in a mixed species meta-analysis. by Nicholas Schaffer (21376843)

Table 1_Analysis and validation of characteristic genes in RNA sequencing datasets from heart failure patients based on multiple algorithms.docx by Yuxuan Li (1674307)

Image 1_Analysis and validation of characteristic genes in RNA sequencing datasets from heart failure patients based on multiple algorithms.tif by Yuxuan Li (1674307)

Exploring Human Brain Metabolism via Genome-Scale Metabolic Modeling with Highlights on Multiple Sclerosis by Mustafa Sertbas (18211859)

“…In parallel with advances in isolation and measurement technologies, genome-scale metabolic models (GEMs) have become a powerful tool in the studies of systems biology to provide critical insights into the understanding of sophisticated eukaryotic systems. In this study, brain cell-specific GEMs were reconstructed for neurons, astrocytes, microglia, oligodendrocytes, and oligodendrocyte precursor cells by integrating single-cell RNA-seq data and global Human1 via a task-driven integrative network inference for tissues (tINIT) algorithm. …”

Exploring Human Brain Metabolism via Genome-Scale Metabolic Modeling with Highlights on Multiple Sclerosis by Mustafa Sertbas (18211859)

“…In parallel with advances in isolation and measurement technologies, genome-scale metabolic models (GEMs) have become a powerful tool in the studies of systems biology to provide critical insights into the understanding of sophisticated eukaryotic systems. In this study, brain cell-specific GEMs were reconstructed for neurons, astrocytes, microglia, oligodendrocytes, and oligodendrocyte precursor cells by integrating single-cell RNA-seq data and global Human1 via a task-driven integrative network inference for tissues (tINIT) algorithm. …”