T
Tao Huang
Researcher at Chinese Academy of Sciences
Publications - 325
Citations - 12593
Tao Huang is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Medicine & Biology. The author has an hindex of 41, co-authored 248 publications receiving 10196 citations. Previous affiliations of Tao Huang include CAS-MPG Partner Institute for Computational Biology & Shanghai Mental Health Center.
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Selection of reprogramming factors of induced pluripotent stem cells based on the protein interaction network and functional profiles.
TL;DR: A fast computational framework was developed by optimize the reprogramming factors via the protein interaction network and gene functional profiles that will become a very useful tool for both basic research and drug development.
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Network-Based Method for Identifying Co- Regeneration Genes in Bone, Dentin, Nerve and Vessel Tissues.
TL;DR: A network-based method to identify co-regeneration genes for bone, dentin, nerve and vessel was constructed based on an extensive network of protein–protein interactions and a total of seventeen genes were inferred, which were deemed to contribute to co-Regeneration of at least two tissues.
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Sedentary behaviors, psychological status, and sleep quality in Chinese university students
TL;DR: Wang et al. as discussed by the authors investigated the independent associations of three types of sedentary behavior with depression, anxiety, and sleep quality among 214 Chinese university students and found that longer smartphone use was associated with worse SDS, SAS, and PSQI scores.
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Analysis of Gene Expression Differences between Different Pancreatic Cells
TL;DR: This study investigated the gene expression of pancreatic cells in six types, tried to identify differentially expressed genes among different cell types, and obtained pancreatic cell biomarkers.
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EMDLP: Ensemble multiscale deep learning model for RNA methylation site prediction
TL;DR: Wang et al. as mentioned in this paper proposed an ensemble multiscale deep learning predictor (EMDLP) to identify RNA methylation sites in an NLP and DL way, which organically combines the dilated convolution and bidirectional LSTM (BiLSTM), which helps to take better advantage of the local and global information for site prediction.