Automated Author ProfileWang, Haili
Wang, Haili
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 15.1 (sum of 20 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
Authors
- Wang, Li ;
- Zhang, Lingli ;
- Lan, Haojia ;
- Wang, Haili ;
- Zhang, Wenhui ;
- Luo, Feng
Multiple myeloma (MM) is a highly heterogeneous disease. Cuproptosis is a novel mode of death that is closely associated with several diseases, such as hepatocellular carcinoma. However, its role in MM is unknown. MM transcriptomic and clinical data were obtained from UCSC Xena and gene expression omnibus (GEO) databases. Following MM samples were divided into different subtypes based on the cuproptosis genes, the differentially expressed genes (DEGs) among different subtypes, namely, candidate cuproptosis related genes were analyzed by univariate Cox and least absolute shrinkage and selection operator (LASSO) regression to construct a cuproptosis-related risk model. After the independent prognostic analysis was performed, a nomogram was constructed. Finally, Functional enrichment analysis and immune infiltration analysis were performed in the high- and low-risk groups, potential therapeutic agents were then predicted. The 784 MM samples in UCSC Xena cohorts were divided into three different subtypes, and 4 out of 346 candidate cuproptosis related genes, namely CDKN2A, BCL3, KCNA3 and TTC14 were used to construct a risk model. Risk score was considered a reliable independent prognostic factor for MM patients. It was investigated that the pathway of cell cycle was significantly enriched in the high-risk group. In addition, immune score, ESTIMATE score and cytolytic activity were significantly different between different risk groups, as well as 13 immune cells such as memory B cells. Nine drugs were predicted in our study. A cuproptosis-related prognostic model was constructed, which may have a potential guiding role in the treatment of MM.
Authors
- Wang, Haili ;
- Zhang, Guoxiang ;
- Dong, Lu ;
- Chen, Lu ;
- Liang, Li ;
- Ge, Li ;
- Gai, Dongzheng ;
- Shen, Xuliang
Multiple myeloma (MM) is a highly heterogeneous disease. Cuproptosis is a novel mode of death that is closely associated with several diseases, such as hepatocellular carcinoma. However, its role in MM is unknown. MM transcriptomic and clinical data were obtained from UCSC Xena and gene expression omnibus (GEO) databases. Following MM samples were divided into different subtypes based on the cuproptosis genes, the differentially expressed genes (DEGs) among different subtypes, namely, candidate cuproptosis related genes were analyzed by univariate Cox and least absolute shrinkage and selection operator (LASSO) regression to construct a cuproptosis-related risk model. After the independent prognostic analysis was performed, a nomogram was constructed. Finally, Functional enrichment analysis and immune infiltration analysis were performed in the high- and low-risk groups, potential therapeutic agents were then predicted. The 784 MM samples in UCSC Xena cohorts were divided into three different subtypes, and 4 out of 346 candidate cuproptosis related genes, namely CDKN2A, BCL3, KCNA3 and TTC14 were used to construct a risk model. Risk score was considered a reliable independent prognostic factor for MM patients. It was investigated that the pathway of cell cycle was significantly enriched in the high-risk group. In addition, immune score, ESTIMATE score and cytolytic activity were significantly different between different risk groups, as well as 13 immune cells such as memory B cells. Nine drugs were predicted in our study. A cuproptosis-related prognostic model was constructed, which may have a potential guiding role in the treatment of MM.
Authors
- Wang, Haili ;
- Zhang, Guoxiang ;
- Dong, Lu ;
- Chen, Lu ;
- Liang, Li ;
- Ge, Li ;
- Gai, Dongzheng ;
- Shen, Xuliang
No description available
Authors
- Wang, Ruirui ;
- Wang, Haili ;
- Wang, Juan ;
- Bai, Feifei ;
- Ma, Yue ;
- Li, Licun ;
- Wang, Qinglun ;
- Zhao, Bin ;
- Cheng, Peng
No description available
Authors
- Wang, Ruirui ;
- Wang, Haili ;
- Wang, Juan ;
- Bai, Feifei ;
- Ma, Yue ;
- Li, Licun ;
- Wang, Qinglun ;
- Zhao, Bin ;
- Cheng, Peng
No description available
Authors
- Wang, Haili ;
- Cai, Shaokun ;
- Ai, Wenna ;
- Xu, Xiufang ;
- Li, Bin ;
- Wang, Baiquan
No description available
Authors
- Wang, Haili ;
- Cai, Shaokun ;
- Ai, Wenna ;
- Xu, Xiufang ;
- Li, Bin ;
- Wang, Baiquan
No description available
Authors
- Wang, Haili ;
- Cai, Shaokun ;
- Ai, Wenna ;
- Xu, Xiufang ;
- Li, Bin ;
- Wang, Baiquan
No description available
Authors
- Wang, Haili ;
- Cai, Shaokun ;
- Ai, Wenna ;
- Xu, Xiufang ;
- Li, Bin ;
- Wang, Baiquan