Alberto Paccanaro

10.3k total citations · 1 hit paper
45 papers, 2.6k citations indexed

About

Alberto Paccanaro is a scholar working on Molecular Biology, Computational Theory and Mathematics and Artificial Intelligence. According to data from OpenAlex, Alberto Paccanaro has authored 45 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Molecular Biology, 9 papers in Computational Theory and Mathematics and 8 papers in Artificial Intelligence. Recurrent topics in Alberto Paccanaro's work include Bioinformatics and Genomic Networks (24 papers), Machine Learning in Bioinformatics (11 papers) and Gene expression and cancer classification (10 papers). Alberto Paccanaro is often cited by papers focused on Bioinformatics and Genomic Networks (24 papers), Machine Learning in Bioinformatics (11 papers) and Gene expression and cancer classification (10 papers). Alberto Paccanaro collaborates with scholars based in United Kingdom, United States and Brazil. Alberto Paccanaro's co-authors include Haiyuan Yu, Tamás Nepusz, Mark Gerstein, Diego Galeano, Alfonso E. Romero, Geoffrey E. Hinton, M Snyder, Valery Trifonov, Long Lu and Yu Xia and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Nature Communications.

In The Last Decade

Alberto Paccanaro

42 papers receiving 2.5k citations

Hit Papers

align trajectories sort by overperformance

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.

Detecting overlapping protein complexes in protein-protein interaction networks

2012 919 citations Tamás Nepusz, Haiyuan Yu et al. Nature Methods profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Alberto Paccanaro United Kingdom	21	1.9k	530	234	232	196	45	2.6k
Md. Altaf‐Ul‐Amin Japan	17	1.5k 0.8×	377 0.7×	82 0.4×	310 1.3×	181 0.9×	77	2.1k
Ali Masoudi‐Nejad Iran	34	2.4k 1.2×	961 1.8×	330 1.4×	407 1.8×	205 1.0×	165	3.7k
Ina Koch Germany	26	2.1k 1.1×	325 0.6×	181 0.8×	100 0.4×	133 0.7×	107	3.3k
Steffen Klamt Germany	42	5.8k 3.0×	602 1.1×	112 0.5×	81 0.3×	302 1.5×	121	6.6k
Sophia Tsoka United Kingdom	25	1.3k 0.7×	217 0.4×	180 0.8×	67 0.3×	100 0.5×	86	2.4k
Assaf Gottlieb United States	20	1.5k 0.8×	877 1.7×	293 1.3×	66 0.3×	92 0.5×	47	2.5k
Xiaochen Bo China	31	2.7k 1.4×	567 1.1×	245 1.0×	256 1.1×	360 1.8×	166	4.2k
Herbert M. Sauro United States	36	3.8k 2.0×	183 0.3×	139 0.6×	160 0.7×	495 2.5×	136	4.3k
Gabriel F. Berriz United States	12	2.3k 1.2×	295 0.6×	53 0.2×	90 0.4×	280 1.4×	15	2.8k
Arnaud Céol Italy	19	2.5k 1.3×	539 1.0×	101 0.4×	56 0.2×	201 1.0×	30	2.7k

Countries citing papers authored by Alberto Paccanaro

Since Specialization

Citations

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

Fields of papers citing papers by Alberto Paccanaro

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alberto Paccanaro

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

All Works

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20 of 20 papers shown

Malchiodi, Dario, et al.. (2025). Fine-tuning of conditional Transformers improves in silico enzyme prediction and generation. Computational and Structural Biotechnology Journal. 27. 1318–1334.

Cernuzzi, Luca, et al.. (2025). ClusterONE Web: a tool for discovering and analyzing overlapping protein complexes. Nucleic Acids Research. 53(W1). W172–W177.

Galeano, Diego & Alberto Paccanaro. (2022). Machine learning prediction of side effects for drugs in clinical trials. Cell Reports Methods. 2(12). 100358–100358. 27 indexed citations

Galeano, Diego, et al.. (2021). A Recommender System Approach for Predicting Effective Antivirals. 1–10. 1 indexed citations

Torres, Mateo, et al.. (2021). Machine learning and network medicine approaches for drug repositioning for COVID-19. Patterns. 3(1). 100396–100396. 31 indexed citations

Gliozzo, Jessica, Paolo Perlasca, Marco Mesiti, et al.. (2020). Network modeling of patients' biomolecular profiles for clinical phenotype/outcome prediction. Scientific Reports. 10(1). 3612–3612. 7 indexed citations

Paccanaro, Alberto, et al.. (2019). Disease gene prediction for molecularly uncharacterized diseases. PLoS Computational Biology. 15(7). e1007078–e1007078. 20 indexed citations

Romero, Alfonso E., et al.. (2015). A network medicine approach to quantify distance between hereditary disease modules on the interactome. Scientific Reports. 5(1). 17658–17658. 14 indexed citations

Romero, Alfonso E., Samuel Heron, Haixuan Yang, et al.. (2014). GOssTo: a stand-alone application and a web tool for calculating semantic similarities on the Gene Ontology. Bioinformatics. 30(15). 2235–2236. 34 indexed citations

10.

Nepusz, Tamás, Haiyuan Yu, & Alberto Paccanaro. (2012). Detecting overlapping protein complexes in protein-protein interaction networks. Nature Methods. 9(5). 471–472. 919 indexed citations breakdown →

11.

Yang, Haixuan, Tamás Nepusz, & Alberto Paccanaro. (2012). Improving GO semantic similarity measures by exploring the ontology beneath the terms and modelling uncertainty. Bioinformatics. 28(10). 1383–1389. 60 indexed citations

12.

Dóczi, Róbert, László Ökrész, Alfonso E. Romero, Alberto Paccanaro, & László Bögre. (2012). Exploring the evolutionary path of plant MAPK networks. Trends in Plant Science. 17(9). 518–525. 87 indexed citations

13.

Abbruscato, Pamela, Tamás Nepusz, Luca Mizzi, et al.. (2012). OsWRKY22 , a monocot WRKY gene, plays a role in the resistance response to blast. Molecular Plant Pathology. 13(8). 828–841. 81 indexed citations

14.

Bhat, Prajwal, Haixuan Yang, László Bögre, Alessandra Devoto, & Alberto Paccanaro. (2012). Computational Selection of Transcriptomics Experiments Improves Guilt-by-Association Analyses. PLoS ONE. 7(8). e39681–e39681. 2 indexed citations

15.

Gianoulis, Tara A., Jeroen Raes, Robert Bjornson, et al.. (2009). Quantifying environmental adaptation of metabolic pathways in metagenomics. Proceedings of the National Academy of Sciences. 106(5). 1374–1379. 139 indexed citations

16.

Waite, Richard, et al.. (2006). Clustering of Pseudomonas aeruginosa transcriptomes from planktonic cultures, developing and mature biofilms reveals distinct expression profiles. BMC Genomics. 7(1). 162–162. 122 indexed citations

17.

Paccanaro, Alberto. (2006). Spectral clustering of protein sequences. Nucleic Acids Research. 34(5). 1571–1580. 119 indexed citations

18.

Gianoulis, Tara A., Yang Liu, Jianrong Li, et al.. (2006). Integration of curated databases to identify genotype-phenotype associations. BMC Genomics. 7(1). 257–257. 29 indexed citations

19.

Paccanaro, Alberto & Geoffrey E. Hinton. (2001). Learning Hierarchical Structures with Linear Relational Embedding. Neural Information Processing Systems. 857–864. 5 indexed citations

20.

Paccanaro, Alberto & Geoffrey E. Hinton. (2000). Learning Distributed Representations by Mapping Concepts and Relations into a Linear Space. International Conference on Machine Learning. 711–718. 3 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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