Standout Papers

scGNN is a novel graph neural network framework for single-cell RNA-Seq analyses 2021 2026 2022 2024217
  1. scGNN is a novel graph neural network framework for single-cell RNA-Seq analyses (2021)
    Juexin Wang, Anjun Ma et al. Nature Communications

Immediate Impact

4 from Science/Nature 58 standout
Sub-graph 1 of 23

Citing Papers

Alzheimer’s Disease Detection Using Deep Learning on Neuroimaging: A Systematic Review
2024 Standout
Survey of spectral clustering based on graph theory
2024 Standout
1 intermediate paper

Works of Ren Qi being referenced

A spectral clustering with self-weighted multiple kernel learning method for single-cell RNA-seq data
2020
scREAD: A Single-Cell RNA-Seq Database for Alzheimer's Disease
2020

Author Peers

Author Last Decade Papers Cites
Ren Qi 484 123 42 97 12 575
Yafei Lyu 372 81 46 82 16 522
Yungang Xu 462 125 21 37 28 612
Wenpin Hou 349 91 53 53 28 557
Alberto Valdeolivas 444 57 87 52 13 608
Adam McDermaid 448 83 52 31 16 623
Danila Bredikhin 505 90 61 78 7 587
Ceri E. Van Slyke 492 42 35 54 16 642
Álvaro Mateos 434 38 48 37 10 644
Haoyang Li 286 66 56 30 35 633
Anna Danese 540 115 112 153 8 622

All Works

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2026