Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
The Heidelberg classification of renal cell tumours
19971.0k citationsGyula Kovács, Mohammed Akhtar et al.The Journal of Pathologyprofile →
This map shows the geographic impact of Göran Roos'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 Göran Roos with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Göran Roos more than expected).
This network shows the impact of papers produced by Göran Roos. 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 Göran Roos. The network helps show where Göran Roos may publish in the future.
Co-authorship network of co-authors of Göran Roos
This figure shows the co-authorship network connecting the top 25 collaborators of Göran Roos.
A scholar is included among the top collaborators of Göran Roos based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Göran Roos. Göran Roos is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
All Works
20 of 20 papers shown
1.
Saarela, Maria & Göran Roos. (2017). Succeeding in the Asian luxury food market. 28(4). 60–63.6 indexed citations
2.
Kettle, John, et al.. (2012). Is the Australian pulp and paper industry still at the crossroads. Appita journal. 65(3). 222–229.4 indexed citations
3.
Roos, Göran & Stephen Pike. (2011). The relationship between university research and firm innovation. Swinburne Research Bank (Swinburne University of Technology).4 indexed citations
Heyman, Mats, Per Frisk, Irina Golovleva, et al.. (2008). Vascular density in childhood acute lymphoblastic leukemia correlates to biological factors and outcome. Leukemia.
10.
Pike, Stephen, Göran Roos, & Bernard Marr. (2005). Strategic Management of Intangible Assets and Value Drivers in R&D Organizations. SSRN Electronic Journal.32 indexed citations
11.
Pul, Carola van, et al.. (2004). Diffusion tensor MRI in neonatal ischernic brain damage: Changes of apparent diffusion coefficient and fractional anisotropy. Pediatric Research. 55(4).1 indexed citations
12.
Marr, Bernard, Göran Roos, Andy Neely, Stephen Pike, & Oliver Gupta. (2004). Hacia la tercera generación en la medida de resultados. 31–46.1 indexed citations
13.
Fernström, Lisa & Göran Roos. (2003). Differences in value creating logics and their managerial consequences: the case of authors, publishers and printers. Swinburne Research Bank (Swinburne University of Technology).1 indexed citations
14.
Tobin, Gerard, Ulf Thunberg, Amy E. Knight Johnson, et al.. (2002). V(a)3-21 gene utilizing chronic lymphocytic leukemias display restricted V lambda 2-14 gene usage and homologous CDR3s.. Blood. 100(11). 362.4 indexed citations
15.
Dragonetti, Nicola Carlo & Göran Roos. (1998). La evaluación de Ausindustry y el business network programme: una perspectiva desde el capital intelectual. Boletín de Estudios Económicos. 53(164). 265–280.10 indexed citations
16.
Kovács, Gyula, Mohammed Akhtar, Bruce Beckwith, et al.. (1997). The Heidelberg classification of renal cell tumours. The Journal of Pathology. 183(2). 131–133.1041 indexed citations breakdown →
17.
Lundblad, Dan, G. Landberg, Göran Roos, & Erik Lundgren. (1991). Ki-67 as a marker for cell cycle regulation by interferon.. PubMed. 11(6). 2131–6.2 indexed citations
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.