Morteza Mohammad-Noori
- Molecular Biology
- Computational Theory and Mathematics top 5%
- Genetics
- Artificial Intelligence
- Cancer Research
- Co-authors
- Mahmoud GhandiM BeerDongwon LeeJavad ZahiriReza EbrahimpourAli Masoudi‐NejadLevi A. GarrawayJames D. Currie
- Topics
- RNA and protein synthesis mechanisms (4 papers)Genomics and Phylogenetic Studies (4 papers)Machine Learning in Bioinformatics (3 papers)
- Cited by
- Molecular BiologyComputational Theory and MathematicsDiscrete Mathematics and Combinatorics
- Partner nations
- IranUnited StatesFrance
In The Last Decade
Morteza Mohammad-Noori
14 papers receiving 758 citations
Peers
Comparison fields: 5 of 70
- Molecular Biology 682
- Computational Theory and Mathematics 104
- Genetics 67
- Artificial Intelligence 57
- Cancer Research 45
Countries citing papers authored by Morteza Mohammad-Noori
This map shows the geographic impact of Morteza Mohammad-Noori'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 Morteza Mohammad-Noori with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Morteza Mohammad-Noori more than expected).
Fields of papers citing papers by Morteza Mohammad-Noori
This network shows the impact of papers produced by Morteza Mohammad-Noori. 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 Morteza Mohammad-Noori. The network helps show where Morteza Mohammad-Noori may publish in the future.
Co-authorship network of co-authors of Morteza Mohammad-Noori
This figure shows the co-authorship network connecting the top 25 collaborators of Morteza Mohammad-Noori. A scholar is included among the top collaborators of Morteza Mohammad-Noori based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Morteza Mohammad-Noori. Morteza Mohammad-Noori is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 38 | |
| 2 | 109 | |
| 3 | 328 | |
| 4 | 47 | |
| 5 | 24 | |
| 6 | 34 | |
| 7 | 125 | |
| 8 | 5 | |
| 9 | 8 | |
| 10 | Some remarks about the derivation operator and generalized Stirling numbers. | 8 |
| 11 | 1 | |
| 12 | 4 | |
| 13 | 30 | |
| 14 | 9 |
About Morteza Mohammad-Noori
Morteza Mohammad-Noori is a scholar working on Discrete Mathematics and Combinatorics, Computational Theory and Mathematics and Algebra and Number Theory, having authored 14 papers that have together received 770 indexed citations. Recurring topics across this work include RNA and protein synthesis mechanisms (4 papers), Genomics and Phylogenetic Studies (4 papers) and Machine Learning in Bioinformatics (3 papers). The work is most often cited by research in Molecular Biology (682 citations), Computational Theory and Mathematics (104 citations) and Discrete Mathematics and Combinatorics (19 citations). Morteza Mohammad-Noori has collaborated with scholars based in Iran, United States and France. Frequent co-authors include Mahmoud Ghandi, M Beer, Dongwon Lee, Javad Zahiri, Reza Ebrahimpour, Ali Masoudi‐Nejad, Levi A. Garraway, James D. Currie, Mohammad Ganjtabesh and Tatyana Goldberg. Their work appears in journals such as Bioinformatics, PLoS Computational Biology and Genomics.
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.