Jacopo Cirrone

624 total citations
9 papers, 311 citations indexed

About

Jacopo Cirrone is a scholar working on Molecular Biology, Plant Science and Surgery. According to data from OpenAlex, Jacopo Cirrone has authored 9 papers receiving a total of 311 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 3 papers in Plant Science and 1 paper in Surgery. Recurrent topics in Jacopo Cirrone's work include Plant Molecular Biology Research (3 papers), Plant nutrient uptake and metabolism (2 papers) and Bioinformatics and Genomic Networks (2 papers). Jacopo Cirrone is often cited by papers focused on Plant Molecular Biology Research (3 papers), Plant nutrient uptake and metabolism (2 papers) and Bioinformatics and Genomic Networks (2 papers). Jacopo Cirrone collaborates with scholars based in United States, Chile and France. Jacopo Cirrone's co-authors include Matthew D. Brooks, Gloria M. Coruzzi, Angelo Pasquino, Dennis Shasha, Shipra Mittal, Kranthi Varala, José M. Álvarez, Sophie Léran, Amy Marshall‐Colón and Molly B. Edwards and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and PLANT PHYSIOLOGY.

In The Last Decade

Jacopo Cirrone

9 papers receiving 306 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Jacopo Cirrone United States	6	249	129	25	13	12	9	311
Shuyan Ding China	10	159 0.6×	357 2.8×	25 1.0×	9 0.7×	5 0.4×	17	421
Angelo Pasquino United States	6	404 1.6×	169 1.3×	31 1.2×	5 0.4×	22 1.8×	6	456
Lihua Jia China	9	217 0.9×	113 0.9×	39 1.6×	2 0.2×	8 0.7×	14	302
María Angels de Luis Balaguer United States	11	254 1.0×	221 1.7×	19 0.8×	11 0.8×	2 0.2×	13	348
Lacey-Anne Sanderson Canada	7	213 0.9×	65 0.5×	25 1.0×	6 0.5×	7 0.6×	10	274
João Vitor Maldonado dos Santos Brazil	7	293 1.2×	112 0.9×	21 0.8×	3 0.2×	11 0.9×	10	331
Abdelhalim Larhlimi Germany	9	78 0.3×	323 2.5×	24 1.0×	8 0.6×	3 0.3×	15	408
Eric Biggers United States	4	299 1.2×	157 1.2×	171 6.8×	9 0.7×	11 0.9×	4	360
Benjamen White United Kingdom	4	224 0.9×	184 1.4×	22 0.9×	6 0.5×	2 0.2×	5	321

Countries citing papers authored by Jacopo Cirrone

Since Specialization

Citations

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

Fields of papers citing papers by Jacopo Cirrone

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jacopo Cirrone

This figure shows the co-authorship network connecting the top 25 collaborators of Jacopo Cirrone. A scholar is included among the top collaborators of Jacopo Cirrone 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 Jacopo Cirrone. Jacopo Cirrone is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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9 of 9 papers shown

Chen, Mei, et al.. (2024). Shifting to machine supervision: annotation-efficient semi and self-supervised learning for automatic medical image segmentation and classification. Scientific Reports. 14(1). 10820–10820. 6 indexed citations

Singh, Pranav, et al.. (2023). Enhancing Medical Image Segmentation: Optimizing Cross-Entropy Weights and Post-Processing with Autoencoders. 2676–2685. 6 indexed citations

Chen, Shengjia, et al.. (2022). Prediction of drug effectiveness in rheumatoid arthritis patients based on machine learning algorithms. 147–154. 1 indexed citations

Brooks, Matthew D., Manpreet S. Katari, José M. Álvarez, et al.. (2020). ConnecTF: A platform to integrate transcription factor–gene interactions and validate regulatory networks. PLANT PHYSIOLOGY. 185(1). 49–66. 38 indexed citations

Cirrone, Jacopo, Matthew D. Brooks, Richard Bonneau, Gloria M. Coruzzi, & Dennis Shasha. (2020). Author Correction: OutPredict: multiple datasets can improve prediction of expression and inference of causality. Scientific Reports. 10(1). 14141–14141. 1 indexed citations

Cirrone, Jacopo, Matthew D. Brooks, Richard Bonneau, Gloria M. Coruzzi, & Dennis Shasha. (2020). OutPredict: multiple datasets can improve prediction of expression and inference of causality. Scientific Reports. 10(1). 6804–6804. 14 indexed citations

Brooks, Matthew D., Jacopo Cirrone, Angelo Pasquino, et al.. (2019). Network Walking charts transcriptional dynamics of nitrogen signaling by integrating validated and predicted genome-wide interactions. Nature Communications. 10(1). 1569–1569. 96 indexed citations

Dessı̀, Danilo, Jacopo Cirrone, Diego Reforgiato Recupero, & Dennis Shasha. (2018). SuperNoder: a tool to discover over-represented modular structures in networks. BMC Bioinformatics. 19(1). 318–318. 3 indexed citations

Varala, Kranthi, Amy Marshall‐Colón, Jacopo Cirrone, et al.. (2018). Temporal transcriptional logic of dynamic regulatory networks underlying nitrogen signaling and use in plants. Proceedings of the National Academy of Sciences. 115(25). 6494–6499. 146 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.

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