What is he best known for?
The fields of study he is best known for:
Christopher H. Contag spends much of his time researching Bioluminescence imaging, In vivo, Immunology, Pathology and Luciferase.
His research integrates issues of Preclinical imaging, Cell, Stem cell, Cell biology and Luciferases in his study of Bioluminescence imaging.
The study incorporates disciplines such as Microbiology, Light source, Reporter gene, Disease and Treatment response in addition to In vivo.
In Immunology, Christopher H. Contag works on issues like Cancer research, which are connected to Adoptive cell transfer, Cellular differentiation, Cytokeratin, Liver Stem Cell and Oncogene.
His studies deal with areas such as Confocal, Cancer, Fluorescein, Bone remodeling and Transplantation as well as Pathology.
His Luciferase research includes themes of Molecular biology, Gene transfer, Gene expression and Bioluminescence.
His most cited work include:
- Adipose-derived adult stromal cells heal critical-size mouse calvarial defects. (772 citations)
- Advances in In Vivo Bioluminescence Imaging of Gene Expression (733 citations)
- MYC inactivation uncovers pluripotent differentiation and tumour dormancy in hepatocellular cancer (668 citations)
What are the main themes of his work throughout his whole career to date?
Christopher H. Contag mainly focuses on In vivo, Pathology, Immunology, Bioluminescence imaging and Cell biology.
His In vivo study combines topics in areas such as Luciferase and Molecular biology.
His work deals with themes such as Gene expression, Transgene and Bioluminescence, which intersect with Luciferase.
His Pathology study frequently involves adjacent topics like Cancer.
His study ties his expertise on Cancer research together with the subject of Immunology.
As part of the same scientific family, he usually focuses on Bioluminescence imaging, concentrating on Stem cell and intersecting with Transplantation.
He most often published in these fields:
- In vivo (25.82%)
- Pathology (19.47%)
- Immunology (15.75%)
What were the highlights of his more recent work (between 2012-2021)?
- Pathology (19.47%)
- In vivo (25.82%)
- Molecular imaging (8.32%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Pathology, In vivo, Molecular imaging, Cell biology and Cancer.
His Pathology research incorporates themes from Raman scattering, Endoscope, Metastasis, Bioluminescence imaging and Endoscopy.
His In vivo research incorporates elements of In vitro and Magnetic resonance imaging.
He combines subjects such as Reporter gene, Medical physics, Computational biology and Medical imaging with his study of Molecular imaging.
The Cell biology study combines topics in areas such as Tumor microenvironment and Molecular biology.
His research investigates the link between Molecular biology and topics such as Luciferase that cross with problems in Cancer research.
Between 2012 and 2021, his most popular works were:
- Differential fates of biomolecules delivered to target cells via extracellular vesicles (234 citations)
- A Raman-based endoscopic strategy for multiplexed molecular imaging (144 citations)
- Non-invasive intravital imaging of cellular differentiation with a bright red-excitable fluorescent protein (143 citations)
In his most recent research, the most cited papers focused on:
His primary scientific interests are in Pathology, In vivo, Cancer, Cell biology and Raman scattering.
His Pathology study integrates concerns from other disciplines, such as Early Cancer Detection, Molecular probe and Fluorescence-lifetime imaging microscopy.
Christopher H. Contag studies Ex vivo, a branch of In vivo.
His work on Tumor microenvironment as part of general Cancer study is frequently linked to Cytokine-induced killer cell, bridging the gap between disciplines.
His work deals with themes such as Molecular biology, Reprogramming and Secretion, which intersect with Cell biology.
His Raman scattering study combines topics from a wide range of disciplines, such as Endoscope and Biomedical engineering.
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.
