What is he best known for?
The fields of study he is best known for:
His primary areas of study are Cancer research, STAT5, Molecular biology, Transcription factor and Signal transduction.
His Cancer research research includes themes of Leukemia, PI3K/AKT/mTOR pathway and Cell growth.
He has included themes like Endocrinology, STAT protein and Tyrosine phosphorylation in his STAT5 study.
His Molecular biology research is multidisciplinary, incorporating perspectives in Mutation, T cell, Mutant, Nuclear receptor coactivator 2 and Regulation of gene expression.
Richard Moriggl interconnects Cancer cell, Senescence, Glucocorticoid receptor and Erythropoiesis in the investigation of issues within Transcription factor.
His studies deal with areas such as Transferrin and Activator as well as Signal transduction.
His most cited work include:
- Stat5 Is Required for IL-2-Induced Cell Cycle Progression of Peripheral T Cells (502 citations)
- Nonredundant roles for Stat5a/b in directly regulating Foxp3 (488 citations)
- Persistent STAT3 activation in colon cancer is associated with enhanced cell proliferation and tumor growth. (289 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Cancer research, STAT5, Cell biology, Leukemia and STAT3.
Richard Moriggl is involved in the study of Cancer research that focuses on Myeloid in particular.
His work carried out in the field of STAT5 brings together such families of science as Molecular biology, Endocrinology, Transcription factor and STAT protein.
As a part of the same scientific study, he usually deals with the Cell biology, concentrating on Cellular differentiation and frequently concerns with Wnt signaling pathway.
The concepts of his Leukemia study are interwoven with issues in Genetically modified mouse, Transgene, Myeloid leukemia and Lymphoma.
His STAT3 study incorporates themes from Colorectal cancer, Gene knockdown and STAT1.
He most often published in these fields:
- Cancer research (79.57%)
- STAT5 (31.18%)
- Cell biology (20.43%)
What were the highlights of his more recent work (between 2018-2021)?
- Cancer research (79.57%)
- STAT5 (31.18%)
- Cell biology (20.43%)
In recent papers he was focusing on the following fields of study:
Richard Moriggl mainly focuses on Cancer research, STAT5, Cell biology, STAT3 and Leukemia.
His Cancer research research incorporates elements of Cancer, Autocrine signalling, Keratin 8 and Anaplastic large-cell lymphoma, Lymphoma.
His STAT5 study frequently draws connections between related disciplines such as STAT protein.
Richard Moriggl has included themes like Cell, Cellular differentiation, Inflammation, Interferon and Lymphocyte in his Cell biology study.
Richard Moriggl interconnects Transcription factor, Immune system, Prostate cancer, STAT1 and Computational biology in the investigation of issues within STAT3.
His Leukemia study combines topics in areas such as Myeloid, Myeloid leukemia, Transgene and STAT5B.
Between 2018 and 2021, his most popular works were:
- Advances in covalent kinase inhibitors. (29 citations)
- Direct Targeting Options for STAT3 and STAT5 in Cancer (25 citations)
- The ERBB-STAT3 Axis Drives Tasmanian Devil Facial Tumor Disease (24 citations)
In his most recent research, the most cited papers focused on:
His main research concerns Cancer research, Lymphoma, Leukemia, STAT5 and Carcinogenesis.
Richard Moriggl combines subjects such as Cancer, Targeted therapy, Tumor progression, Signal transduction and Anaplastic large-cell lymphoma with his study of Cancer research.
His Lymphoma research is multidisciplinary, incorporating perspectives in Tyrosine kinase, Large cell and Autocrine signalling.
His studies in Leukemia integrate themes in fields like STAT3, Haematopoiesis, Myeloid leukemia and Chromatin remodeling.
His STAT5 research integrates issues from Janus kinase, Endocrinology and STAT protein.
His STAT protein study integrates concerns from other disciplines, such as Liver cancer, Chronic liver disease, Internal medicine, Metabolic syndrome and Fatty liver.
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.
