Mita Mukherjee
Impact in
- Cancer Research top 2%
- Cancer, Hypoxia, and Metabolism
- Cancer-related molecular mechanisms research
- Molecular Biology top 10%
- Metabolism, Diabetes, and Cancer
- Genomics and Chromatin Dynamics
- Epigenetics and DNA Methylation
- RNA Research and Splicing
- RNA modifications and cancer
- Mitochondrial Function and Pathology
Papers in
-
- Cancer-related molecular mechanisms research 5
- Cancer, Hypoxia, and Metabolism 1
-
- RNA and protein synthesis mechanisms 3
- RNA Research and Splicing 2
- Co-authors
- Yi Xu (2 shared papers)Rahul Reddy (1 shared paper)Sunkyu Kim (1 shared paper)Diane R. Wonsey (1 shared paper)Hyunsuk Shim (1 shared paper)Linda A. Lee (1 shared paper)Chi V. Dang (1 shared paper)Qing Li (1 shared paper)
- Journals
- Blood (2 papers)Molecular Cancer Research (2 papers)Molecular and Cellular Biology (1 paper)Breast Cancer Research and Treatment (1 paper)Biochemistry (1 paper)
- Partner nations
- United StatesCanada
In The Last Decade
Mita Mukherjee
9 papers receiving 1.2k citations
Mita Mukherjee's Hit Papers
Peers
Comparison fields: 5 of 77
- Cancer Research 629
- Molecular Biology 921
- Oncology 188
- Immunology 96
- Immunology and Allergy 22
Countries citing papers authored by Mita Mukherjee
This map shows the geographic impact of Mita Mukherjee'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 Mita Mukherjee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mita Mukherjee more than expected).
Fields of papers citing papers by Mita Mukherjee
This network shows the impact of papers produced by Mita Mukherjee. 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 Mita Mukherjee. The network helps show where Mita Mukherjee may publish in the future.
Co-authors
The 25 scholars most cited alongside Mita Mukherjee, 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 | Deregulation of Glucose Transporter 1 and Glycolytic Gene Expression by c-Myc Hit paper breakdown → | 2000 | 738 |
| 2 | 2000 | 157 | |
| 3 | 2008 | 111 | |
| 4 | 2008 | 88 | |
| 5 | 2009 | 67 | |
| 6 | 2002 | 56 | |
| 7 | 1998 | 30 | |
| 8 | 2016 | 5 | |
| 9 | 2008 | 1 | |
| 10 | 2006 | 0 |
About Mita Mukherjee
Mita Mukherjee is a scholar working on Cancer Research, Molecular Biology, Oncology, Immunology and Allergy and Pathology and Forensic Medicine, having authored 10 papers that have together received 1.3k indexed citations. Recurring topics across this work include Cancer-related molecular mechanisms research (5 papers), Cell Adhesion Molecules Research (3 papers), Cytokine Signaling Pathways and Interactions (3 papers), RNA and protein synthesis mechanisms (3 papers), interferon and immune responses (2 papers), Genetic factors in colorectal cancer (2 papers), RNA Research and Splicing (2 papers) and Cancer, Hypoxia, and Metabolism (1 paper). The work is most often cited by research in Cancer Research (629 citations), Molecular Biology (921 citations), Oncology (188 citations), Immunology (96 citations) and Immunology and Allergy (22 citations). Mita Mukherjee has collaborated with scholars based in United States and Canada. Frequent co-authors include Yi Xu, Rahul Reddy, Sunkyu Kim, Diane R. Wonsey, Hyunsuk Shim, Linda A. Lee, Chi V. Dang, Qing Li, Linda Resar and Lisa J. Wood. Their work appears in journals such as Blood, Molecular Cancer Research, Molecular and Cellular Biology, Breast Cancer Research and Treatment and Biochemistry.
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.