I.T. Oliver
Impact in
- Clinical Biochemistry top 0.5%
- Metabolism and Genetic Disorders
- Biochemistry top 2%
Papers in
-
- Mitochondrial Function and Pathology 6
- Biochemical and Molecular Research 4
-
- Diet, Metabolism, and Disease 6
- Co-authors
- D. Yeung (5 shared papers)Patrick G. Holt (7 shared papers)F J Ballard (3 shared papers)George C. Yeoh (11 shared papers)Max H. Cake (5 shared papers)F. A. Bennett (1 shared paper)Gregory R. Donovan (1 shared paper)John A. W. Kirsch (1 shared paper)
- Journals
- Biochemistry (5 papers)FEBS Letters (5 papers)Biochemical Journal (4 papers)Clinica Chimica Acta (2 papers)Nature (2 papers)
- Partner nations
- AustraliaUnited KingdomUnited States
In The Last Decade
I.T. Oliver
55 papers receiving 2.0k citations
I.T. Oliver's Hit Papers
Peers
Comparison fields: 5 of 105
- Clinical Biochemistry 458
- Biochemistry 243
- Cell Biology 370
- Endocrinology, Diabetes and Metabolism 348
- Physiology 465
Countries citing papers authored by I.T. Oliver
This map shows the geographic impact of I.T. Oliver'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 I.T. Oliver with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites I.T. Oliver more than expected).
Fields of papers citing papers by I.T. Oliver
This network shows the impact of papers produced by I.T. Oliver. 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 I.T. Oliver. The network helps show where I.T. Oliver may publish in the future.
Co-authors
The 25 scholars most cited alongside I.T. Oliver, 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 57 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | A spectrophotometric method for the determination of creative phosphokinase and myokinase Hit paper breakdown → | 1955 | 650 |
| 2 | 1963 | 193 | |
| 3 | 1968 | 121 | |
| 4 | 1968 | 110 | |
| 5 | 1967 | 99 | |
| 6 | 1968 | 96 | |
| 7 | 1967 | 75 | |
| 8 | 1969 | 70 | |
| 9 | 1968 | 67 | |
| 10 | 1979 | 67 | |
| 11 | 1963 | 50 | |
| 12 | 1967 | 48 | |
| 13 | 1961 | 48 | |
| 14 | 1971 | 42 | |
| 15 | 1996 | 40 | |
| 16 | 1962 | 38 | |
| 17 | 1967 | 34 | |
| 18 | 1962 | 32 | |
| 19 | 1972 | 31 | |
| 20 | 1979 | 28 |
About I.T. Oliver
I.T. Oliver is a scholar working on Molecular Biology, Endocrinology, Diabetes and Metabolism, Clinical Biochemistry, Surgery and Cell Biology, having authored 57 papers that have together received 2.3k indexed citations. Recurring topics across this work include Metabolism and Genetic Disorders (10 papers), Pancreatic function and diabetes (7 papers), Diet, Metabolism, and Disease (6 papers), Mitochondrial Function and Pathology (6 papers), Aldose Reductase and Taurine (5 papers), Adipose Tissue and Metabolism (4 papers), Biochemical and Molecular Research (4 papers) and Drug Transport and Resistance Mechanisms (4 papers). The work is most often cited by research in Clinical Biochemistry (458 citations), Biochemistry (243 citations), Cell Biology (370 citations), Endocrinology, Diabetes and Metabolism (348 citations) and Physiology (465 citations). I.T. Oliver has collaborated with scholars based in Australia, United Kingdom and United States. Frequent co-authors include D. Yeung, Patrick G. Holt, F J Ballard, George C. Yeoh, Max H. Cake, F. A. Bennett, Gregory R. Donovan, John A. W. Kirsch, J. L. Peel and P.J. Bentley. Their work appears in journals such as Biochemistry, FEBS Letters, Biochemical Journal, Clinica Chimica Acta and Nature.
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.