João Aires‐de‐Sousa

3.5k citations
75 papers · 2.1k indexed · h-index 27
Topics
Computational Drug Discovery Methods (29 papers)Analytical Chemistry and Chromatography (16 papers)Machine Learning in Materials Science (16 papers)
Journals
Angewandte Chemie International EditionSHILAP Revista de lepidopterologíaBioinformatics
Partner nations
PortugalChinaSpain

In The Last Decade

João Aires‐de‐Sousa

74 papers receiving 2.1k citations

Peers

João Aires‐de‐Sousa
Comparison fields: 5 of 151
  • Computational Theory and Mathematics 740
  • Molecular Biology 632
  • Materials Chemistry 505
  • Organic Chemistry 453
  • Spectroscopy 438
Replace Uko Maran with:
Uko Maran Estonia
Vitaly P. Solov’ev Russia
Gilles Marcou France
Probir Kumar Ojha India
Andrea Mauri Italy
Indrani Mitra India
Sulev Sild Estonia
Dimitar A. Dobchev Estonia
V. Е. Kuz’min Ukraine
Maykel Pérez González Cuba
João Aires‐de‐Sousa relative to Uko Maran Estonia Uko Maran's profile →
Citations per field
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Citations per year

Countries citing papers authored by João Aires‐de‐Sousa

Since Specialization
Citations

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

Fields of papers citing papers by João Aires‐de‐Sousa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by João Aires‐de‐Sousa. 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 João Aires‐de‐Sousa. The network helps show where João Aires‐de‐Sousa may publish in the future.

Co-authorship network of co-authors of João Aires‐de‐Sousa

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 12
3 1
4 17
5 19
6 9
7 12
8 37
9 101
10 57
11 2
12 1
13 4
14 45
15 31
16 41
17 22
18 6
19 36
20 26

About João Aires‐de‐Sousa

João Aires‐de‐Sousa is a scholar working on Computational Theory and Mathematics, Spectroscopy and Catalysis, having authored 75 papers that have together received 2.1k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (29 papers), Analytical Chemistry and Chromatography (16 papers) and Machine Learning in Materials Science (16 papers). The work is most often cited by research in Computational Theory and Mathematics (740 citations), Spectroscopy (438 citations) and Catalysis (180 citations). João Aires‐de‐Sousa has collaborated with scholars based in Portugal, China and Spain. Frequent co-authors include Diogo A. R. S. Latino, Qingyou Zhang, Johann Gasteiger, Florbela Pereira, Gonçalo V. S. M. Carrera, Yuri I. Binev, Markus C. Hemmer, Ana M. Lobo, Sunil Gupta and Kaixia Xiao. Their work appears in journals such as Angewandte Chemie International Edition, SHILAP Revista de lepidopterología and Bioinformatics.

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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