Gene Expression And Cancer Classification
90 researchers across 10 institutions
Research in gene expression and cancer classification investigates the complex molecular mechanisms that drive cancer development and progression. Scientists explore how genes are activated or silenced in cancer cells, and how these changes can be used to categorize different types of cancer. This involves employing advanced techniques in genomics, transcriptomics, and bioinformatics to analyze vast datasets of genetic and molecular information. Key areas of study include identifying specific gene signatures associated with cancer subtypes, understanding the role of gene regulation in tumor growth and metastasis, and developing computational models for more accurate cancer diagnosis and prognosis.
This work holds particular relevance for Arkansas by addressing public health challenges and supporting the state's growing biosciences sector. Understanding the genetic underpinnings of cancer can lead to improved diagnostic tools and targeted therapies, potentially benefiting the health of Arkansans. Furthermore, advancements in cancer classification and molecular diagnostics contribute to the economic development of the state's biotechnology and pharmaceutical industries, fostering innovation and creating high-skill employment opportunities.
This research area benefits from extensive interdisciplinary collaboration, drawing upon expertise in molecular biology, computer science, statistics, and clinical medicine. Engagement spans multiple Arkansas institutions, fostering a broad base of knowledge and research activity across the state.
Top Researchers
| Name | Institution | h-index | Citations | Career Stage | Badges |
|---|---|---|---|---|---|
| Fenghuang Zhan | UAMS | 67 | 19,235 | Grant PI High Impact | |
| Dan A. Dixon | UAMS | 46 | 8,552 | High Impact | |
| Volodymyr Tryndyak | NCTR | 44 | 6,689 | High Impact | |
| Kyounghyun Kim | UAMS | 32 | 6,334 | High Impact | |
| Jingwen Li | University of Arkansas | 27 | 2,763 | ||
| Timothy A. Evans | University of Arkansas | 26 | 3,609 | Grant PI High Impact | |
| Ruby Charak | UAMS | 25 | 2,098 | ||
| Kentu Lassiter | University of Arkansas | 21 | 1,566 | High Impact | |
| Samrat Roy Choudhury | UAMS | 20 | 1,531 | High Impact | |
| Elizabeth H. Creyer | University of Arkansas | 20 | 3,462 | ||
| Josephine Bowen | UAMS | 19 | 2,653 | ||
| Mohammad Alinoor Rahman | UAMS | 17 | 1,191 | Grant PI | |
| Horacio Gómez-Acevedo | UAMS | 17 | 1,343 | ||
| Sayem Miah | UAMS | 15 | 517 | ||
| Sara Orlowski | University of Arkansas | 15 | 784 | ||
| Terry Harville | UAMS | 15 | 2,825 | ||
| Jerry G. Jones | UAMS | 15 | 969 | ||
| Ana Clara P. Azevedo‐Pouly | UAMS | 13 | 772 | ||
| Shan Zhao | University of Arkansas | 13 | 764 | ||
| Oscar Zuniga | UAMS | 12 | 416 |
Related Research Areas
Strategic Outlook
Global signals from OpenAlex for this research area: where the field is growing, how concentrated leadership is, and where Arkansas sits relative to the world's top-100 institutions. Descriptive only — surfaced as input to the conversation about where to place bets, not a recommendation. Signal confidence: LOW
Top US institutions in this area
- 1 Harvard University 2,062
- 2 Stanford University 1,458
- 3 National Institutes of Health 1,186
- 4 University of Michigan 1,141
- 5 Johns Hopkins University 1,104
Cross-Institution Connections
Researchers at different institutions with overlapping expertise in Gene Expression And Cancer Classification.