Píetro Lió

33.8k total citations · 4 hit papers
444 papers, 12.8k citations indexed

About

Píetro Lió is a scholar working on Molecular Biology, Artificial Intelligence and Genetics. According to data from OpenAlex, Píetro Lió has authored 444 papers receiving a total of 12.8k indexed citations (citations by other indexed papers that have themselves been cited), including 210 papers in Molecular Biology, 81 papers in Artificial Intelligence and 43 papers in Genetics. Recurrent topics in Píetro Lió's work include Bioinformatics and Genomic Networks (52 papers), Genomics and Phylogenetic Studies (43 papers) and Gene Regulatory Network Analysis (35 papers). Píetro Lió is often cited by papers focused on Bioinformatics and Genomic Networks (52 papers), Genomics and Phylogenetic Studies (43 papers) and Gene Regulatory Network Analysis (35 papers). Píetro Lió collaborates with scholars based in United Kingdom, Italy and United States. Píetro Lió's co-authors include Mohammad Ali Moni, Nick Goldman, Renato Fani, Marco Fondi, Elisa Laurenti, Andreas Trumpp, Richard C. van der Wath, Anne Wilson, Simon Whelan and Pan Hui and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Nucleic Acids Research.

In The Last Decade

Píetro Lió

422 papers receiving 12.4k citations

Hit Papers

align trajectories

What are hit papers?

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.

Hematopoietic Stem Cells Reversibly Switch from Dormancy to Self-Renewal during Homeostasis and Repair

2008 1.4k citations Píetro Lió et al. profile →
A parameter-efficient deep learning approach to predict conversion from mild cognitive impairment to Alzheimer's disease

2019 281 citations Píetro Lió et al. profile →
Machine learning-aided generative molecular design

2024 68 citations Píetro Lió et al. profile →
Structure-based drug design with equivariant diffusion models

2024 52 citations Píetro Lió et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Píetro Lió United Kingdom	53	5.8k	1.5k	1.2k	874	867	444	12.8k
Marcel Reinders Netherlands	54	5.9k 1.0×	1.2k 0.8×	1.1k 0.9×	261 0.3×	908 1.0×	298	11.1k
Jens Timmer Germany	73	6.1k 1.1×	815 0.5×	806 0.7×	232 0.3×	1.1k 1.3×	361	16.5k
Ole Winther Denmark	47	6.4k 1.1×	1.3k 0.9×	885 0.7×	270 0.3×	552 0.6×	205	13.4k
Kevin Lin United States	54	4.2k 0.7×	1.2k 0.8×	617 0.5×	291 0.3×	1.4k 1.6×	333	12.8k
John A. Robinson Switzerland	57	5.5k 1.0×	2.8k 1.9×	700 0.6×	227 0.3×	360 0.4×	414	14.1k
Thomas Lengauer Germany	67	13.5k 2.3×	1.5k 1.0×	2.3k 1.9×	221 0.3×	379 0.4×	360	25.8k
Hong Yan Hong Kong	61	4.6k 0.8×	2.3k 1.6×	309 0.3×	217 0.2×	916 1.1×	960	17.8k
Wing Hung Wong United States	74	14.2k 2.5×	3.8k 2.6×	2.9k 2.4×	296 0.3×	420 0.5×	262	26.7k
Rob Tibshirani United States	19	4.7k 0.8×	1.2k 0.8×	1.2k 1.0×	185 0.2×	289 0.3×	28	14.2k
Sheng Wang China	56	6.8k 1.2×	704 0.5×	695 0.6×	351 0.4×	492 0.6×	360	12.7k

Countries citing papers authored by Píetro Lió

Since Specialization

Citations

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

Fields of papers citing papers by Píetro Lió

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Píetro Lió

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Prinzi, Francesco, Pietro Barbiero, Gennaro Cordasco, et al.. (2024). Using AI explainable models and handwriting/drawing tasks for psychological well-being. Information Systems. 127. 102465–102465.

Lió, Píetro, et al.. (2024). On synergy between ultrahigh throughput screening and machine learning in biocatalyst engineering. Faraday Discussions. 252(0). 89–114. 12 indexed citations

Iuliano, Antonella, et al.. (2024). Denoising Probabilistic Diffusion Models for Synthetic Healthcare Image Generation. CINECA IRIS Institutional Research Information System (University of Basilicata). 415–420.

Rahman, Md Habibur, et al.. (2023). Network based approach to identify interactions between Type 2 diabetes and cancer comorbidities. Life Sciences. 335. 122244–122244. 7 indexed citations

Lu, Xiaofeng, et al.. (2023). GAT-DNS: DNS Multivariate Time Series Prediction Model Based on Graph Attention Network. IRIS Research product catalog (Sapienza University of Rome). 127–131. 4 indexed citations

Viñas, Ramón, et al.. (2021). Adversarial generation of gene expression data. Bioinformatics. 38(3). 730–737. 29 indexed citations

Bica, Ioana, et al.. (2021). CellVGAE: an unsupervised scRNA-seq analysis workflow with graph attention networks. Bioinformatics. 38(5). 1277–1286. 25 indexed citations

Tangherloni, Andrea, et al.. (2021). Analysis of single-cell RNA sequencing data based on autoencoders. BOA (University of Milano-Bicocca). 16 indexed citations

Lu, Xiaofeng, et al.. (2021). A Universal Malicious Documents Static Detection Framework Based on Feature Generalization. Applied Sciences. 11(24). 12134–12134. 5 indexed citations

10.

Lu, Xiaofeng, et al.. (2021). Heterogeneous Model Fusion Federated Learning Mechanism Based on Model Mapping. IEEE Internet of Things Journal. 9(8). 6058–6068. 18 indexed citations

11.

Nanni, Mirco, et al.. (2020). Learning Mobility Flows from Urban Features with Spatial Interaction Models and Neural Networks**To appear in the Proceedings of 2020 IEEE International Conference on Smart Computing (SMARTCOMP 2020). ISTI Open Portal. 15 indexed citations

12.

Lu, Xiaofeng, Xiao Zhou, Meng Wan, Píetro Lió, & Pan Hui. (2020). Domain-Oriented Topic Discovery Based on Features Extraction and Topic Clustering. IEEE Access. 8. 93648–93662. 6 indexed citations

13.

Cangea, Cătălina, Petar Veličković, & Píetro Lió. (2020). XFlow: Cross-Modal Deep Neural Networks for Audiovisual Classification. IRIS Research product catalog (Sapienza University of Rome). 22 indexed citations

14.

Lu, Xiaofeng, et al.. (2020). Privacy-Preserving Asynchronous Federated Learning Mechanism for Edge Network Computing. IEEE Access. 8. 48970–48981. 107 indexed citations

15.

Liberis, Edgar, Petar Veličković, Pietro Sormanni, Michele Vendruscolo, & Píetro Lió. (2018). Parapred: antibody paratope prediction using convolutional and recurrent neural networks. Bioinformatics. 34(17). 2944–2950. 112 indexed citations

16.

Barros, Michael Taynnan, et al.. (2018). Computational Models for Trapping Ebola Virus Using Engineered Bacteria. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 15(6). 2017–2027. 9 indexed citations

17.

Shavit, Yoli & Píetro Lió. (2014). Combining a wavelet change point and the Bayes factor for analysing chromosomal interaction data. Molecular BioSystems. 10(6). 1576–1585. 26 indexed citations

18.

Pratanwanich, Ploy N. & Píetro Lió. (2014). Pathway-based Bayesian inference of drug–disease interactions. Molecular BioSystems. 10(6). 1538–1548. 13 indexed citations

19.

Movassagh, Mehregan, Mun‐Kit Choy, David A. Knowles, et al.. (2011). Distinct Epigenomic Features in End-Stage Failing Human Hearts. Circulation. 124(22). 2411–2422. 217 indexed citations

20.

Thomas, N. Simon, Jennifer Wilkinson, Píetro Lió, et al.. (2000). [Genetic factors involved in asthma and atopy. Studies in British families].. PubMed. 17(1 Pt 2). 177–82.

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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