Shenmin Guan

ORCID: 0000-0001-5786-115X
Publications
Citations
Views
---
Saved
---
About
Contact & Profiles
Research Areas
  • Hemoglobinopathies and Related Disorders
  • Blood groups and transfusion
  • Imbalanced Data Classification Techniques
  • Diverse Scientific Research Studies
  • Genetic diversity and population structure
  • Plant Molecular Biology Research
  • Plant Gene Expression Analysis
  • Prenatal Screening and Diagnostics
  • Ecology and Vegetation Dynamics Studies
  • Plant Disease Resistance and Genetics
  • Iron Metabolism and Disorders
  • Plant and animal studies

Shenzhen University Health Science Center
2019

East China Normal University
2011

Long dormancy period of seeds limits the large-scale artificial cultivation scarce Paris polyphylla var. yunnanensis, an important traditional Chinese medicine. Characterizing miRNAs and their targets is crucial to understanding role during seed in this species. Considering limited genome information species, we first sequenced assembled transcriptome data dormant coats as reference genome. A total 146,671 unigenes with average length 923 bp were identified showed functional diversity based...

10.3390/ijms18010219 article EN International Journal of Molecular Sciences 2017-01-22

Machine intelligence (MI), including machine learning and deep learning, have been regarded as promising methods to reduce the prohibitively high cost of drug development. However, a dilemma within MI has limited its wide application: models are easier interpret but yield worse predictive performance than models. Therefore, we propose pipeline called Class Imbalance Learning with Bayesian Optimization (CILBO) improve in discovery. To demonstrate efficacy CILBO pipeline, developed an example...

10.1038/s41598-022-05717-7 article EN cc-by Scientific Reports 2022-02-08

Abstract Regional gender differences in autosomal chromosome disorders have been observed repeatedly. However, the corresponding diversity changes remain unconfirmed. By analyzing previously published thalassemia data from Dai people Dehong and Xishuangbanna (two regions Yunnan Province, China), we found that several sequence types, including HBA CNV HBB mutations, significantly depend on but not Dehong. With supportive evidence previous researches, accept some certain mutations regionally....

10.1038/s41598-019-41905-8 article EN cc-by Scientific Reports 2019-04-02
Coming Soon ...