Mary Qu Yang
- Molecular Biology top 5%
- Machine Learning in Bioinformatics 27
- Gene expression and cancer classification 23
- Bioinformatics and Genomic Networks 15
- Genomics and Phylogenetic Studies 12
- Protein Structure and Dynamics 10
- RNA and protein synthesis mechanisms 10
- Cancer Research top 5%
- Cancer-related molecular mechanisms research 11
- Cancer Genomics and Diagnostics 8
- Artificial Intelligence top 5%
- Co-authors
- Jack YangYouping DengA. Keith DunkerLaura ElnitskiLiangjiang WangVladimir N. UverskyJingwei MengChristopher J. Oldfield
- Journals
- Nucleic Acids Research (1 paper)SHILAP Revista de lepidopterología (1 paper)PLoS ONE (1 paper)
- Partner nations
- United StatesChinaRussia
In The Last Decade
Mary Qu Yang
114 papers receiving 2.6k citations
Peers
Comparison fields: 5 of 167
- Molecular Biology 1.9k
- Cancer Research 319
- Computational Theory and Mathematics 139
- Artificial Intelligence 269
- Applied Microbiology and Biotechnology 17
Countries citing papers authored by Mary Qu Yang
This map shows the geographic impact of Mary Qu 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 Mary Qu Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mary Qu Yang more than expected).
Fields of papers citing papers by Mary Qu Yang
This network shows the impact of papers produced by Mary Qu 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 Mary Qu Yang. The network helps show where Mary Qu Yang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Mary Qu 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 | 2024 | 3 | |
| 2 | 2018 | 24 | |
| 3 | 2018 | 16 | |
| 4 | 2018 | 6 | |
| 5 | 2016 | 9 | |
| 6 | 2010 | 1 | |
| 7 | 2010 | 19 | |
| 8 | 2009 | 98 | |
| 9 | 2008 | 32 | |
| 10 | 2008 | 20 | |
| 11 | 2008 | 35 | |
| 12 | 2008 | 19 | |
| 13 | 2008 | 1 | |
| 14 | 2008 | 7 | |
| 15 | 2008 | 493 | |
| 16 | 2008 | 8 | |
| 17 | Orthology and Multiple Class Prediction of Functional Elements in the Human Genome. | 2007 | 0 |
| 18 | Classification of Brain Glioma by Using Neural Networks Ensemble with Multi-Task Learning. | 2007 | 1 |
| 19 | Feature Selection for Co-Training: A QSAR Study. | 2007 | 1 |
| 20 | Identification of Intrinsically Unstructured Regions in Proteins Using Primary Structure. | 2006 | 1 |
About Mary Qu Yang
Mary Qu Yang is a scholar working on Cancer Research, Molecular Biology and Applied Microbiology and Biotechnology, having authored 120 papers that have together received 2.7k indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (27 papers), Gene expression and cancer classification (23 papers), Bioinformatics and Genomic Networks (15 papers), Genomics and Phylogenetic Studies (12 papers), Cancer-related molecular mechanisms research (11 papers), Protein Structure and Dynamics (10 papers), RNA and protein synthesis mechanisms (10 papers) and Cancer Genomics and Diagnostics (8 papers). The work is most often cited by research in Molecular Biology (1.9k citations), Cancer Research (319 citations) and Computational Theory and Mathematics (139 citations). Mary Qu Yang has collaborated with scholars based in United States, China and Russia. Frequent co-authors include Jack Yang, Youping Deng, A. Keith Dunker, Laura Elnitski, Liangjiang Wang, Vladimir N. Uversky, Jingwei Meng, Christopher J. Oldfield, Mehdi Pirooznia and Caiyan Huang. Their work appears in journals such as Nucleic Acids Research, SHILAP Revista de lepidopterología and PLoS ONE.
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.