Qicheng Ma
- Cancer Research top 5%
- Molecular Biology top 5%
- Machine Learning in Bioinformatics 6
- CRISPR and Genetic Engineering 4
- Genomics and Phylogenetic Studies 3
- Bioinformatics and Genomic Networks 2
- Fractal and DNA sequence analysis 2
- RNA and protein synthesis mechanisms 2
- Aging top 5%
- Biochemistry top 5%
- Immunology top 10%
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- Topic Modeling 2
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- Chromosomal and Genetic Variations 2
- Co-authors
- Peter M. FinanJessica L. YeciesPichai RamanBrendan D. ManningMatthew G. Vander HeidenClary B. ClishAmanda L. SouzaSuchithra Menon
- Partner nations
- United StatesSwitzerlandChina
In The Last Decade
Qicheng Ma
22 papers receiving 2.6k citations
Hit Papers
Peers
Comparison fields: 5 of 112
- Cancer Research 554
- Molecular Biology 1.8k
- Aging 40
- Biochemistry 109
- Immunology 308
Countries citing papers authored by Qicheng Ma
This map shows the geographic impact of Qicheng Ma'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 Qicheng Ma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qicheng Ma more than expected).
Fields of papers citing papers by Qicheng Ma
This network shows the impact of papers produced by Qicheng Ma. 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 Qicheng Ma. The network helps show where Qicheng Ma may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Qicheng Ma, 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 | 2 | |
| 2 | 2023 | 2 | |
| 3 | 2022 | 22 | |
| 4 | 2021 | 22 | |
| 5 | 2020 | 15 | |
| 6 | 2019 | 19 | |
| 7 | 2019 | 31 | |
| 8 | ZNRF3 promotes Wnt receptor turnover in an R-spondin-sensitive mannerbreakdown → | 2012 | 709 |
| 9 | Activation of a Metabolic Gene Regulatory Network Downstream of mTOR Complex 1 | 2010 | 2 |
| 10 | Activation of a Metabolic Gene Regulatory Network Downstream of mTOR Complex 1breakdown → | 2010 | 1582 |
| 11 | 2008 | 13 | |
| 12 | A Utility-Based Approach to Bandwidth Allocation and Link Scheduling in Wireless Networks | 2007 | 8 |
| 13 | 2005 | 13 | |
| 14 | 2001 | 29 | |
| 15 | Evaluating the Significance of Sequence Motifs by the Minimum Description Length Principle | 2000 | 2 |
| 16 | 2000 | 1 | |
| 17 | 2000 | 1 | |
| 18 | 2000 | 31 | |
| 19 | Application of Bayesian Neural Networks to Protein Sequence Classification. | 1999 | 3 |
| 20 | 1999 | 9 |
About Qicheng Ma
Qicheng Ma is a scholar working on Aging, Molecular Biology and Rehabilitation, having authored 22 papers that have together received 2.6k indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (6 papers), CRISPR and Genetic Engineering (4 papers), Genomics and Phylogenetic Studies (3 papers), Topic Modeling (2 papers), Bioinformatics and Genomic Networks (2 papers), Chromosomal and Genetic Variations (2 papers), Fractal and DNA sequence analysis (2 papers) and RNA and protein synthesis mechanisms (2 papers). The work is most often cited by research in Cancer Research (554 citations), Molecular Biology (1.8k citations) and Aging (40 citations). Qicheng Ma has collaborated with scholars based in United States, Switzerland and China. Frequent co-authors include Peter M. Finan, Jessica L. Yecies, Pichai Raman, Brendan D. Manning, Matthew G. Vander Heiden, Clary B. Clish, Amanda L. Souza, Suchithra Menon, Leon O. Murphy and Jeffrey P. MacKeigan.
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.