Sergio Bacallado

46 total papers · 1.9k total citations
19 papers, 352 citations indexed

About

Sergio Bacallado is a scholar working on Molecular Biology, Artificial Intelligence and Statistics and Probability. According to data from OpenAlex, Sergio Bacallado has authored 19 papers receiving a total of 352 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 8 papers in Artificial Intelligence and 8 papers in Statistics and Probability. Recurrent topics in Sergio Bacallado's work include Bayesian Methods and Mixture Models (8 papers), Protein Structure and Dynamics (6 papers) and Statistical Methods and Bayesian Inference (4 papers). Sergio Bacallado is often cited by papers focused on Bayesian Methods and Mixture Models (8 papers), Protein Structure and Dynamics (6 papers) and Statistical Methods and Bayesian Inference (4 papers). Sergio Bacallado collaborates with scholars based in United States, United Kingdom and Italy. Sergio Bacallado's co-authors include Vijay S. Pande, Gregory R. Bowman, Xuhui Huang, John D. Chodera, José Miguel Hernández-Lobato, Gregor N. C. Simm, Lorenzo Trippa, Andreas Bender, Stefano Favaro and Susan Holmes and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and The Journal of Chemical Physics.

In The Last Decade

Sergio Bacallado

17 papers receiving 347 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Sergio Bacallado 227 70 68 57 42 19 352
David Allouche 224 1.0× 68 1.0× 49 0.7× 25 0.4× 40 1.0× 17 380
Ge Yunhui 266 1.2× 79 1.1× 75 1.1× 65 1.1× 7 0.2× 28 351
Julian Lee 259 1.1× 160 2.3× 33 0.5× 38 0.7× 19 0.5× 22 392
Yukito Iba 157 0.7× 91 1.3× 11 0.2× 35 0.6× 64 1.5× 24 374
Wei Wang 214 0.9× 73 1.0× 32 0.5× 65 1.1× 13 0.3× 11 306
Pierre Monmarché 103 0.5× 44 0.6× 42 0.6× 13 0.2× 35 0.8× 47 401
Tarık Çelik 128 0.6× 103 1.5× 17 0.3× 41 0.7× 16 0.4× 25 346
T. J. Christopher Ward 210 0.9× 72 1.0× 22 0.3× 61 1.1× 15 0.4× 10 339
Steven Lettieri 170 0.7× 49 0.7× 32 0.5× 33 0.6× 10 0.2× 11 301
Marco Zamparo 298 1.3× 96 1.4× 17 0.3× 13 0.2× 9 0.2× 26 370

Countries citing papers authored by Sergio Bacallado

Since Specialization
Citations

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

Fields of papers citing papers by Sergio Bacallado

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sergio Bacallado

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

All Works

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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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