Hui Wan
6 Papers
Hui Wan is an academic researcher. The author has contributed to research in topics: Computer science & Medicine. The author has an hindex of 2, co-authored 4 publications.
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Papers
scNAME: neighborhood contrastive clustering with ancillary mask estimation for scRNA-seq data
Hui Wan,Liang Chen,Min Deng +2 more
TL;DR: This work proposes a novel scRNA-seq clustering algorithm called scNAME which incorporates a mask estimation task for gene pertinence mining and a neighborhood contrastive learning framework for cell intrinsic structure exploitation, among the first to introduce a gene relationship exploration strategy, as well as a global cellular similarity repository, in the single-cell field.
scEMAIL: Universal and Source-free Annotation Method for scRNA-seq Data with Novel Cell-type Perception
Hui Wan,Liang Chen,Min Deng +2 more
TL;DR: Wang et al. as mentioned in this paper proposed a universal annotation framework for single-cell RNA sequencing (scRNA-seq) data called scEMAIL, which automatically detects novel cell types without accessing source data during adaptation.
8
Integrative analysis of transcriptome and yeast screening system identified heat stress-responding genes in ryegrass
TL;DR: In this paper , the authors reveal the continuous changes in gene expression levels in ryegrass at the whole-genome level during the process of high temperature response, showing that there was a general inhibition of photosynthesis-related gene expression level over time, whereas the expression levels of endoplasmic reticulum protein processing-related genes were primarily induced.
7
SPANN: annotating single-cell resolution spatial transcriptome data with scRNA-seq data.
Musu Yuan,Hui Wan,Zihao Wang,Qirui Guo,Min Deng +4 more
TL;DR: The main tasks of SPANN are to transfer cell-type labels from well-annotated scRNA-seq data to newly generated single-cell resolution spatial transcriptome data and discover novel cells from spatial data and conduct cell-type-level alignment.
1
Continually adapting pre-trained language model to universal annotation of single-cell RNA-seq data
Hui Wan,Musu Yuan,Yiwei Fu,Min Deng +3 more
TL;DR: A universal cell-type annotation tool, called CANAL, that continuously fine-tunes a pre-trained language model trained on a large amount of unlabeled scRNA-seq data, as new well-labeled data emerges, alleviating the dilemma of catastrophic forgetting.