A. John Barrett
Impact in
- Hematology top 0.02%
- Hematopoietic Stem Cell Transplantation
- Acute Myeloid Leukemia Research
- Cancer Research top 0.05%
- Protease and Inhibitor Mechanisms
Papers in
- Hematology 166
- Hematopoietic Stem Cell Transplantation 118
- Acute Myeloid Leukemia Research 45
- Oncology 157
- Peptidase Inhibition and Analysis 85
- Co-authors
- Neil D. Rawlings (42 shared papers)Richard W. Farndale (2 shared papers)David J. Buttle (24 shared papers)Alex Bateman (7 shared papers)Heidrun Kirschke (5 shared papers)P M Starkey (11 shared papers)M A Brown (13 shared papers)ROBERT FINN (2 shared papers)
- Journals
- Biochemical Journal (70 papers)Blood (65 papers)Biology of Blood and Marrow Transplantation (27 papers)British Journal of Haematology (26 papers)Bone Marrow Transplantation (18 papers)
- Partner nations
- United StatesUnited KingdomSweden
In The Last Decade
A. John Barrett
532 papers receiving 44.2k citations
A. John Barrett's Hit Papers
Peers
Comparison fields: 5 of 184
- Hematology 8.0k
- Cancer Research 7.0k
- Biotechnology 3.3k
- Oncology 8.8k
- Immunology and Allergy 1.8k
Countries citing papers authored by A. John Barrett
This map shows the geographic impact of A. John Barrett'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 A. John Barrett with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites A. John Barrett more than expected).
Fields of papers citing papers by A. John Barrett
This network shows the impact of papers produced by A. John Barrett. 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 A. John Barrett. The network helps show where A. John Barrett may publish in the future.
Co-authors
The 25 scholars most cited alongside A. John Barrett, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 540 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Improved quantitation and discrimination of sulphated glycosaminoglycans by use of dimethylmethylene blue Hit paper breakdown → | 1986 | 2984 |
| 2 | [41] Cathepsin B, cathepsin H, and cathepsin L Hit paper breakdown → | 1981 | 1561 |
| 3 | MEROPS: the database of proteolytic enzymes, their substrates and inhibitors Hit paper breakdown → | 2011 | 1279 |
| 4 | A Direct Spectrophotometric Microassay for Sulfated Glycosaminoglycans in Cartilage Cultures Hit paper breakdown → | 1982 | 1217 |
| 5 | The MEROPS database of proteolytic enzymes, their substrates and inhibitors in 2017 and a comparison with peptidases in the PANTHER database Hit paper breakdown → | 2017 | 1202 |
| 6 | The interaction of α2-macroglobulin with proteinases. Characteristics and specificity of the reaction, and a hypothesis concerning its molecular mechanism Hit paper breakdown → | 1973 | 946 |
| 7 | The Handbook of proteolytic enzymes Hit paper breakdown → | 1998 | 939 |
| 8 | L-trans-Epoxysuccinyl-leucylamido(4-guanidino)butane (E-64) and its analogues as inhibitors of cysteine proteinases including cathepsins B, H and L Hit paper breakdown → | 1982 | 934 |
| 9 | MEROPS: the peptidase database Hit paper breakdown → | 2009 | 740 |
| 10 | MEROPS: the database of proteolytic enzymes, their substrates and inhibitors Hit paper breakdown → | 2013 | 726 |
| 11 | Evolutionary families of peptidases Hit paper breakdown → | 1993 | 673 |
| 12 | [13] Evolutionary families of metallopeptidases Hit paper breakdown → | 1995 | 638 |
| 13 | Twenty years of theMEROPSdatabase of proteolytic enzymes, their substrates and inhibitors Hit paper breakdown → | 2015 | 529 |
| 14 | [2] Families of serine peptidases Hit paper breakdown → | 1994 | 502 |
| 15 | The electrophoretically ‘slow’ and ‘fast’ forms of the α2-macroglobulin molecule Hit paper breakdown → | 1979 | 500 |
| 16 | 2004 | 472 | |
| 17 | Isolation of six cysteine proteinase inhibitors from human urine. Their physicochemical and enzyme kinetic properties and concentrations in biological fluids. Hit paper breakdown → | 1986 | 438 |
| 18 | Proteinases in Mammalian Cells and Tissues Hit paper breakdown → | 1977 | 435 |
| 19 | 2007 | 433 | |
| 20 | A new assay for cathepsin B1 and other thiol proteinases Hit paper breakdown → | 1972 | 370 |
About A. John Barrett
A. John Barrett is a scholar working on Hematology, Oncology, Molecular Biology, Immunology and Cancer Research, having authored 540 papers that have together received 46.0k indexed citations. Recurring topics across this work include Hematopoietic Stem Cell Transplantation (118 papers), Peptidase Inhibition and Analysis (85 papers), Protease and Inhibitor Mechanisms (72 papers), Immune Cell Function and Interaction (54 papers), Acute Myeloid Leukemia Research (45 papers), T-cell and B-cell Immunology (41 papers), Enzyme Production and Characterization (38 papers) and Immunotherapy and Immune Responses (36 papers). The work is most often cited by research in Hematology (8.0k citations), Cancer Research (7.0k citations), Biotechnology (3.3k citations), Oncology (8.8k citations) and Immunology and Allergy (1.8k citations). A. John Barrett has collaborated with scholars based in United States, United Kingdom and Sweden. Frequent co-authors include Neil D. Rawlings, Richard W. Farndale, David J. Buttle, Alex Bateman, Heidrun Kirschke, P M Starkey, M A Brown, ROBERT FINN, Christopher G. Knight and J. Frederick Woessner. Their work appears in journals such as Biochemical Journal, Blood, Biology of Blood and Marrow Transplantation, British Journal of Haematology and Bone Marrow Transplantation.
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.