Sulaiman Sheriff

121 papers receiving 2.8k citations

Peers

Sulaiman Sheriff
Comparison fields: 5 of 114
  • Molecular Biology 898
  • Radiology, Nuclear Medicine and Imaging 806
  • Cellular and Molecular Neuroscience 782
  • Physiology 463
  • Endocrine and Autonomic Systems 455
Replace Akihiko Wada with:
Akihiko Wada Japan
Jian‐Qiang Lu Canada
Ujendra Kumar Canada
Christiane Charriaut‐Marlangue France
P.R. Bär Netherlands
Heiko Backes Germany
Richard A. Hawkins United States
Vincent Lebon France
Matthias T. Wyss Switzerland
Andrew A. Parsons United Kingdom
Sulaiman Sheriff relative to Akihiko Wada Japan Akihiko Wada's profile →
Citations per field
00.5×1.5×2.3×
Akihiko Wada · 1×
Citations per year

Countries citing papers authored by Sulaiman Sheriff

Since Specialization
Citations

This map shows the geographic impact of Sulaiman Sheriff'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 Sulaiman Sheriff with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sulaiman Sheriff more than expected).

Fields of papers citing papers by Sulaiman Sheriff

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sulaiman Sheriff. 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 Sulaiman Sheriff. The network helps show where Sulaiman Sheriff may publish in the future.

Co-authorship network of co-authors of Sulaiman Sheriff

This figure shows the co-authorship network connecting the top 25 collaborators of Sulaiman Sheriff. A scholar is included among the top collaborators of Sulaiman Sheriff 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 Sulaiman Sheriff. Sulaiman Sheriff 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
#WorkIndexed citations
1 7
2 11
3 1
4 4
5 2
6 22
7 16
8 32
9 56
10 33
11 61
12 31
13
Evaluation of three neural network models using Wisconsin breast cancer database
7
14 14
15 24
16 4
17 7
18 28
19 44
20 17

About Sulaiman Sheriff

Sulaiman Sheriff is a scholar working on Endocrine and Autonomic Systems, Radiology, Nuclear Medicine and Imaging and Cellular and Molecular Neuroscience, having authored 121 papers that have together received 2.9k indexed citations. Recurring topics across this work include Advanced MRI Techniques and Applications (41 papers), Neuropeptides and Animal Physiology (28 papers) and Receptor Mechanisms and Signaling (18 papers). The work is most often cited by research in Endocrine and Autonomic Systems (455 citations), Cellular and Molecular Neuroscience (782 citations) and Radiology, Nuclear Medicine and Imaging (806 citations). Sulaiman Sheriff has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Andrew A. Maudsley, Ambikaipakan Balasubramaniam, A. Balasubramaniam, Hassane Amlal, William T. Chance, Hong Du, Gregory A. Grabowski, Josef E. Fischer, Mohammed Goryawala and Lou Ann Friend. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Journal of Clinical Oncology.

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.

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