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
-
- Metabolism and Genetic Disorders 10
- Co-authors
- D. Yeung (5 shared papers)Patrick G. Holt (7 shared papers)F J Ballard (3 shared papers)George C. Yeoh (10 shared papers)Max H. Cake (4 shared papers)F. A. Bennett (1 shared paper)Gregory R. Donovan (1 shared paper)John A. W. Kirsch (1 shared paper)
- Journals
- FEBS Letters (5 papers)Biochemistry (5 papers)Biochemical Journal (4 papers)Neonatology (3 papers)Nature (2 papers)
- Partner nations
- AustraliaUnited KingdomUnited States
In The Last Decade
I.T. Oliver
55 papers receiving 1.9k citations
I.T. Oliver's Hit Papers
Peers
Comparison fields: 5 of 102
- Clinical Biochemistry 445
- Biochemistry 221
- Cell Biology 338
- Endocrinology, Diabetes and Metabolism 331
- Physiology 439
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 55 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 | 626 |
| 2 | 1963 | 175 | |
| 3 | 1968 | 107 | |
| 4 | 1967 | 98 | |
| 5 | 1968 | 92 | |
| 6 | 1968 | 88 | |
| 7 | 1967 | 68 | |
| 8 | 1979 | 65 | |
| 9 | 1969 | 64 | |
| 10 | 1968 | 63 | |
| 11 | 1963 | 46 | |
| 12 | 1967 | 45 | |
| 13 | 1961 | 44 | |
| 14 | 1962 | 36 | |
| 15 | 1996 | 34 | |
| 16 | 1971 | 33 | |
| 17 | 1967 | 31 | |
| 18 | 1972 | 30 | |
| 19 | 1962 | 26 | |
| 20 | 1979 | 25 |
About I.T. Oliver
I.T. Oliver is a scholar working on Molecular Biology, Clinical Biochemistry, Endocrinology, Diabetes and Metabolism, Cell Biology and Surgery, having authored 55 papers that have together received 2.2k indexed citations. Recurring topics across this work include Metabolism and Genetic Disorders (10 papers), Mitochondrial Function and Pathology (6 papers), Pancreatic function and diabetes (5 papers), Diet, Metabolism, and Disease (5 papers), Aldose Reductase and Taurine (5 papers), Biochemical and Molecular Research (4 papers), Drug Transport and Resistance Mechanisms (4 papers) and Fatty Acid Research and Health (3 papers). The work is most often cited by research in Clinical Biochemistry (445 citations), Biochemistry (221 citations), Cell Biology (338 citations), Endocrinology, Diabetes and Metabolism (331 citations) and Physiology (439 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 Anthony Trewavas. Their work appears in journals such as FEBS Letters, Biochemistry, Biochemical Journal, Neonatology 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.