Leaderboards/machine learning in bioinformatics

machine learning in bioinformatics

Last updated June 2, 2026

Rising Stars

New and hot

Rising Stars Researchers

1
Peilin Guo
Institute of Process Engineering
99
2
Wei Wei
Institute of Process Engineering
90
3
Dongming Yan
First Affiliated Hospital of Zhengzhou University
70
4
Shuhong Guan
The First People's Hospital of Changzhou
60
5
Chun Feng
Zunyi Medical University
40
6
Ayoub Vaziri-Moghadam
Sharif University of Technology
30
7
Mohammad-Hadi Foroughmand-Araabi
Sharif University of Technology
20
8
Tianhao Li
Tianjin First Center Hospital
10

Rising Stars Papers

Insufficient data

Emerging Leaders

Gaining momentum

Emerging Leaders Researchers

1
Alex Chklovski
Translational Research Institute
99
2
Hao Chen
University of California, Riverside
90
3
Daniel Buchan
University College London
80
4
Zahra Mohtasham‐Amiri
Islamic Azad University of Tabriz
70
5
JiangFei Zhou
Jinan University
60
6
Hongshuo Shi
Shanghai University of Traditional Chinese Medicine
50
7
Yukun Li
Capital Medical University
40
8
Zixuan Wu
Hunan University of Traditional Chinese Medicine
30
9
Matheus Cezimbra Barbieri
Universidade Federal do Rio Grande do Sul
20
10
Yuanming Yang
Guangzhou University of Chinese Medicine
10

Emerging Leaders Papers

1
A novel Alzheimer’s disease prognostic signature: identification and analysis of glutamine metabolism genes in immunogenicity and immunotherapy efficacy
Scientific Reports|2023
57 cit.

All-Time Leaders

The canon

All-Time Leaders Researchers

1
Jürgen Cox
Max Planck Institute of Biochemistry
90
2
H. Sebastian Seung
Princeton University
70
3
Pu-Feng Du
Tianjin University of Science and Technology
60
4
Xiaoyi Lv
Xinjiang University
50
5
Mohammad Ali Moni
The University of Sydney
40
6
Xiao Yu
Central South University
30
7
Nizamettin Aydın
Yıldız Technical University
20
8
Faizan Younas
Khwaja Fareed University of Engineering and Information Technology
10

All-Time Leaders Papers

1
Performance measures in evaluating machine learning based bioinformatics predictors for classifications
Quantitative Biology|2016
303 cit.

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