What is he best known for?
The fields of study he is best known for:
Tak W. Mak mostly deals with Cell biology, Molecular biology, Immunology, Cancer research and Cytotoxic T cell.
His Cell biology research is multidisciplinary, incorporating perspectives in Apoptosis, Transcription factor and Caspase 8.
His Molecular biology study incorporates themes from T cell, Thymocyte, T-cell receptor and Transcription, Gene.
His research in Immunology intersects with topics in Receptor and Cellular differentiation.
Tak W. Mak works mostly in the field of Cancer research, limiting it down to concerns involving PTEN and, occasionally, Protein kinase B.
His research in Cytotoxic T cell tackles topics such as CD8 which are related to areas like Major histocompatibility complex.
His most cited work include:
- OPGL is a key regulator of osteoclastogenesis, lymphocyte development and lymph-node organogenesis (2875 citations)
- Immunologic Self-Tolerance Maintained by Cd25+Cd4+Regulatory T Cells Constitutively Expressing Cytotoxic T Lymphocyte–Associated Antigen 4 (1916 citations)
- Induction and activation of the transcription factor NFATc1 (NFAT2) integrate RANKL signaling in terminal differentiation of osteoclasts. (1856 citations)
What are the main themes of his work throughout his whole career to date?
Tak W. Mak focuses on Cell biology, Immunology, Molecular biology, Cancer research and T cell.
The concepts of his Cell biology study are interwoven with issues in Apoptosis, Programmed cell death, Cellular differentiation and Transcription factor.
The study of Immunology is intertwined with the study of Receptor in a number of ways.
His studies in Molecular biology integrate themes in fields like T lymphocyte, Thymocyte, CD8, Gene and T-cell receptor.
His Cancer research research integrates issues from Carcinogenesis, Cancer, Tumor suppressor gene, Kinase and PTEN.
Many of his studies involve connections with topics such as Cytotoxic T cell and T cell.
He most often published in these fields:
- Cell biology (33.67%)
- Immunology (30.51%)
- Molecular biology (28.88%)
What were the highlights of his more recent work (between 2014-2021)?
- Cancer research (31.02%)
- Cell biology (33.67%)
- Immune system (19.18%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Cancer research, Cell biology, Immune system, Immunology and Cancer.
His studies deal with areas such as Carcinogenesis, Cell, Mitosis and Cancer cell as well as Cancer research.
As a member of one scientific family, Tak W. Mak mostly works in the field of Cell biology, focusing on Downregulation and upregulation and, on occasion, Cell growth.
His Immune system study combines topics in areas such as Blockade, Disease and Neuroscience.
His work carried out in the field of Immunology brings together such families of science as Receptor and Programmed cell death.
Tak W. Mak combines subjects such as Tumor necrosis factor alpha and Autoimmunity with his study of Inflammation.
Between 2014 and 2021, his most popular works were:
- Regulation of tumour necrosis factor signalling: live or let die (449 citations)
- Regulation of tumour necrosis factor signalling: live or let die (449 citations)
- Single-Cell Genomics Unveils Critical Regulators of Th17 Cell Pathogenicity (344 citations)
In his most recent research, the most cited papers focused on:
Tak W. Mak spends much of his time researching Cancer research, Immunology, Immune system, Cell biology and Receptor.
Tak W. Mak has researched Cancer research in several fields, including Mitosis, Genome instability, Proinflammatory cytokine, STAT3 and Triple-negative breast cancer.
Tak W. Mak has researched Immunology in several fields, including Endocrinology, Internal medicine and Lipocalin.
His Immune system study frequently draws connections between related disciplines such as Cytotoxic T cell.
A large part of his Cell biology studies is devoted to Hippo signaling.
The study incorporates disciplines such as Tumor microenvironment, Downregulation and upregulation and Signal transduction in addition to Receptor.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
