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.
Identification of differential RNA modifications from nanopore direct RNA sequencing with xPore
2021197 citationsPloy N. Pratanwanich, Yuk Kei Wan et al.profile →
Detection of m6A from direct RNA sequencing using a multiple instance learning framework
2022144 citationsChristopher Hendra, Ploy N. Pratanwanich et al.Nature Methodsprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Alexandre H. Thiéry
Since
Specialization
Citations
This map shows the geographic impact of Alexandre H. Thiéry'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 Alexandre H. Thiéry with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alexandre H. Thiéry more than expected).
Fields of papers citing papers by Alexandre H. Thiéry
This network shows the impact of papers produced by Alexandre H. Thiéry. 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 Alexandre H. Thiéry. The network helps show where Alexandre H. Thiéry may publish in the future.
Co-authorship network of co-authors of Alexandre H. Thiéry
This figure shows the co-authorship network connecting the top 25 collaborators of Alexandre H. Thiéry.
A scholar is included among the top collaborators of Alexandre H. Thiéry 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 Alexandre H. Thiéry. Alexandre H. Thiéry is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Hendra, Christopher, Ploy N. Pratanwanich, Yuk Kei Wan, et al.. (2022). Detection of m6A from direct RNA sequencing using a multiple instance learning framework. Nature Methods. 19(12). 1590–1598.144 indexed citations breakdown →
Tun, Tin A., Shamira Perera, Ching‐Yu Cheng, et al.. (2021). Use of Artificial Intelligence to Describe the Structural Signature of the Glaucomatous Optic Nerve Head. Investigative Ophthalmology & Visual Science. 62(8). 1030–1030.1 indexed citations
9.
Girard, Michaël J. A., Alexandre H. Thiéry, Lasse Malmqvist, et al.. (2020). Deep Learning OCT-based Detection and Quantification of Optic Disc Drusen allows Discrimination from True Papilledema. Investigative Ophthalmology & Visual Science. 61(7). 4029–4029.1 indexed citations
Thiéry, Alexandre H., et al.. (2019). On the relationship between variational inference and adaptive importance sampling.. arXiv (Cornell University).1 indexed citations
13.
Girard, Michaël J. A., Khai Sing Chin, Tin Aung, et al.. (2018). Deep Learning can Exploit 3D Structural Information of the Optic Nerve Head to Provide a Glaucoma Diagnostic Power Superior to that of Retinal Nerve Fibre Layer Thickness. Investigative Ophthalmology & Visual Science. 59(9). 4081–4081.2 indexed citations
Pillai, Natesh S., Andrew M. Stuart, & Alexandre H. Thiéry. (2011). Optimal Proposal Design for Random Walk Type Metropolis Algorithms with Gaussian Random Field Priors. arXiv (Cornell University).1 indexed citations
20.
Pillai, Natesh S., Andrew M. Stuart, & Alexandre H. Thiéry. (2011). On the random walk metropolis algorithm for Gaussian random field priors and the gradient flow. arXiv (Cornell University).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.