Jack Yang
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- Electrocatalysts for Energy Conversion 19
- Advanced Photocatalysis Techniques 11
- Materials Chemistry top 2%
- Molecular Biology top 5%
- Machine Learning in Bioinformatics 32
- Gene expression and cancer classification 29
- Bioinformatics and Genomic Networks 20
- Protein Structure and Dynamics 19
- Catalysis top 5%
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- Perovskite Materials and Applications 12
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- Computational Drug Discovery Methods 11
- Co-authors
- Mary Qu YangSean LiA. Keith DunkerJingwei MengChristopher J. OldfieldVladimir N. UverskyWenxian LiYouping Deng
- Partner nations
- United StatesChinaAustralia
In The Last Decade
Jack Yang
183 papers receiving 6.0k citations
Hit Papers
Peers
Comparison fields: 5 of 182
- Renewable Energy, Sustainability and the Environment 969
- Materials Chemistry 2.0k
- Molecular Biology 2.5k
- Catalysis 210
- Electrical and Electronic Engineering 1.4k
Countries citing papers authored by Jack Yang
This map shows the geographic impact of Jack Yang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jack Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jack Yang more than expected).
Fields of papers citing papers by Jack Yang
This network shows the impact of papers produced by Jack Yang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jack Yang. The network helps show where Jack Yang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Jack Yang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 0 | |
| 4 | 2024 | 0 | |
| 5 | 2024 | 3 | |
| 6 | 2023 | 32 | |
| 7 | 2023 | 4 | |
| 8 | 2023 | 3 | |
| 9 | 2022 | 30 | |
| 10 | 2022 | 28 | |
| 11 | 2022 | 23 | |
| 12 | 2022 | 40 | |
| 13 | 2022 | 66 | |
| 14 | 2021 | 80 | |
| 15 | 2017 | 153 | |
| 16 | The unfoldomics decade: an update on intrinsically disordered proteins | 2008 | 13 |
| 17 | Intrinsic Disorder in Protein-Protein Interaction Networks: Case Studies of Complexes Involving p53 and 14-3-3. | 2007 | 8 |
| 18 | Classification of Brain Glioma by Using Neural Networks Ensemble with Multi-Task Learning. | 2007 | 1 |
| 19 | Evolving MIMO Flexible Neural Trees for Nonlinear System Identification. | 2007 | 7 |
| 20 | Feature Selection for Co-Training: A QSAR Study. | 2007 | 1 |
About Jack Yang
Jack Yang is a scholar working on Catalysis, Renewable Energy, Sustainability and the Environment, Molecular Biology, Materials Chemistry and Cancer Research, having authored 193 papers that have together received 6.1k indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (32 papers), Gene expression and cancer classification (29 papers), Bioinformatics and Genomic Networks (20 papers), Protein Structure and Dynamics (19 papers), Electrocatalysts for Energy Conversion (19 papers), Perovskite Materials and Applications (12 papers), Computational Drug Discovery Methods (11 papers) and Advanced Photocatalysis Techniques (11 papers). The work is most often cited by research in Renewable Energy, Sustainability and the Environment (969 citations), Materials Chemistry (2.0k citations), Molecular Biology (2.5k citations), Catalysis (210 citations) and Electrical and Electronic Engineering (1.4k citations). Jack Yang has collaborated with scholars based in United States, China and Australia. Frequent co-authors include Mary Qu Yang, Sean Li, A. Keith Dunker, Jingwei Meng, Christopher J. Oldfield, Vladimir N. Uversky, Wenxian Li, Youping Deng, Zhimin Ao and S. Li. Their work appears in journals such as BMC Genomics, Chemical Physics Letters, BMC Systems Biology, BMC Bioinformatics and The Journal of Physical Chemistry C.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.