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.
Improved protein structure prediction using potentials from deep learning
20202.0k citationsAndrew Senior, John Jumper et al.Natureprofile →
Pushing the frontiers of density functionals by solving the fractional electron problem
2021243 citationsJames Kirkpatrick, David H. P. Turban et al.Scienceprofile →
Unveiling the predictive power of static structure in glassy systems
2020230 citationsVictor Bapst, Thomas M. Keck et al.Nature Physicsprofile →
Protein structure prediction using multiple deep neural networks in the 13th Critical Assessment of Protein Structure Prediction (CASP13)
2019208 citationsAndrew Senior, John Jumper et al.Proteins Structure Function and Bioinformaticsprofile →
Citations per year, relative to Alexander Nelson Alexander Nelson (= 1×)
peers
Payel Das
Countries citing papers authored by Alexander Nelson
Since
Specialization
Citations
This map shows the geographic impact of Alexander Nelson'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 Alexander Nelson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alexander Nelson more than expected).
Fields of papers citing papers by Alexander Nelson
This network shows the impact of papers produced by Alexander Nelson. 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 Alexander Nelson. The network helps show where Alexander Nelson may publish in the future.
Co-authorship network of co-authors of Alexander Nelson
This figure shows the co-authorship network connecting the top 25 collaborators of Alexander Nelson.
A scholar is included among the top collaborators of Alexander Nelson 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 Alexander Nelson. Alexander Nelson is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
All Works
8 of 8 papers shown
1.
Kirkpatrick, James, David H. P. Turban, Alexander L. Gaunt, et al.. (2021). Pushing the frontiers of density functionals by solving the fractional electron problem. Science. 374(6573). 1385–1389.243 indexed citations breakdown →
2.
Bapst, Victor, Thomas M. Keck, Agnieszka Grabska‐Barwińska, et al.. (2020). Unveiling the predictive power of static structure in glassy systems. Nature Physics. 16(4). 448–454.230 indexed citations breakdown →
3.
Senior, Andrew, John Jumper, James Kirkpatrick, et al.. (2020). Improved protein structure prediction using potentials from deep learning. Nature. 577(7792). 706–710.2026 indexed citations breakdown →
Senior, Andrew, John Jumper, James Kirkpatrick, et al.. (2019). Protein structure prediction using multiple deep neural networks in the 13th Critical Assessment of Protein Structure Prediction (CASP13). Proteins Structure Function and Bioinformatics. 87(12). 1141–1148.208 indexed citations breakdown →
6.
Nelson, Alexander. (2007). Principles Of Agricultural Botany.
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.