Alain Tchagang

720 total citations
57 papers, 471 citations indexed

About

Alain Tchagang is a scholar working on Molecular Biology, Materials Chemistry and Computational Theory and Mathematics. According to data from OpenAlex, Alain Tchagang has authored 57 papers receiving a total of 471 indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Molecular Biology, 27 papers in Materials Chemistry and 17 papers in Computational Theory and Mathematics. Recurrent topics in Alain Tchagang's work include Machine Learning in Materials Science (26 papers), Gene expression and cancer classification (17 papers) and Computational Drug Discovery Methods (15 papers). Alain Tchagang is often cited by papers focused on Machine Learning in Materials Science (26 papers), Gene expression and cancer classification (17 papers) and Computational Drug Discovery Methods (15 papers). Alain Tchagang collaborates with scholars based in Canada, United States and Brazil. Alain Tchagang's co-authors include Yeong Yoo, Ahmed H. Tewfik, Michel Nganbe, Yifeng Li, Dennis R. Salahub, Maicon Pierre Lourenço, Youlian Pan, Jiří Hostaš, Andreas M. Köster and Patrizia Calaminici and has published in prestigious journals such as The Journal of Chemical Physics, The Journal of Physical Chemistry C and IEEE Transactions on Signal Processing.

In The Last Decade

Alain Tchagang

53 papers receiving 459 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Alain Tchagang Canada 14 181 167 122 101 52 57 471
Rajasekaran Ekambaram India 10 147 0.8× 37 0.2× 89 0.7× 25 0.2× 7 0.1× 41 417
Yanning Wang China 12 86 0.5× 128 0.8× 183 1.5× 31 0.3× 31 0.6× 28 471
Oufan Zhang United States 7 158 0.9× 388 2.3× 59 0.5× 104 1.0× 12 0.2× 16 591
Michael Krein United States 8 240 1.3× 302 1.8× 65 0.5× 152 1.5× 14 0.3× 19 659
Martin Ginkel Germany 11 376 2.1× 75 0.4× 155 1.3× 50 0.5× 12 0.2× 21 626
Shichao Xu China 12 80 0.4× 64 0.4× 70 0.6× 22 0.2× 7 0.1× 43 350
Yanan Liu China 12 79 0.4× 145 0.9× 163 1.3× 9 0.1× 10 0.2× 49 560
Maryam Abbasi Portugal 9 106 0.6× 66 0.4× 21 0.2× 131 1.3× 10 0.2× 55 299
Jeffrey Law United States 6 416 2.3× 40 0.2× 32 0.3× 35 0.3× 8 0.2× 13 530
Yiheng Zhu China 12 292 1.6× 75 0.4× 50 0.4× 66 0.7× 5 0.1× 40 637

Countries citing papers authored by Alain Tchagang

Since Specialization
Citations

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

Fields of papers citing papers by Alain Tchagang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alain Tchagang

This figure shows the co-authorship network connecting the top 25 collaborators of Alain Tchagang. A scholar is included among the top collaborators of Alain Tchagang 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 Alain Tchagang. Alain Tchagang 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
1.
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Lourenço, Maicon Pierre, Jiří Hostaš, Colin Bellinger, Alain Tchagang, & Dennis R. Salahub. (2024). Reinforcement learning for in silico determination of adsorbate—substrate structures. Journal of Computational Chemistry. 45(15). 1289–1302. 1 indexed citations
3.
Nganbe, Michel, et al.. (2024). A deep generative modeling architecture for designing lattice-constrained perovskite materials. npj Computational Materials. 10(1). 12 indexed citations
4.
5.
Hostaš, Jiří, Patrizia Calaminici, Maicon Pierre Lourenço, et al.. (2023). How important is the amount of exact exchange for spin-state energy ordering in DFT? Case study of molybdenum carbide cluster, Mo4C2. The Journal of Chemical Physics. 159(18). 3 indexed citations
6.
Nganbe, Michel, et al.. (2023). An evolutionary variational autoencoder for perovskite discovery. Frontiers in Materials. 10. 6 indexed citations
7.
Tchagang, Alain, et al.. (2023). Examining multi-objective deep reinforcement learning frameworks for molecular design. Biosystems. 232. 104989–104989. 4 indexed citations
8.
Lourenço, Maicon Pierre, Alain Tchagang, Karthik Shankar, Venkataraman Thangadurai, & Dennis R. Salahub. (2023). Active learning for optimum experimental design—insight into perovskite oxides. Canadian Journal of Chemistry. 101(9). 734–744. 5 indexed citations
9.
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Lourenço, Maicon Pierre, Jiří Hostaš, Patrizia Calaminici, et al.. (2022). Automatic structural elucidation of vacancies in materials by active learning. Physical Chemistry Chemical Physics. 24(41). 25227–25239. 10 indexed citations
11.
Lourenço, Maicon Pierre, Jiří Hostaš, Patrizia Calaminici, et al.. (2022). GAMaterial—A genetic‐algorithm software for material design and discovery. Journal of Computational Chemistry. 44(7). 814–823. 15 indexed citations
12.
Tchagang, Alain, et al.. (2022). Multi-Objective Drug Design Based on Graph-Fragment Molecular Representation and Deep Evolutionary Learning. Frontiers in Pharmacology. 13. 920747–920747. 24 indexed citations
13.
Tchagang, Alain, et al.. (2022). Adversarial deep evolutionary learning for drug design. Biosystems. 222. 104790–104790. 4 indexed citations
14.
Hostaš, Jiří, Alain Tchagang, Maicon Pierre Lourenço, Andreas M. Köster, & Dennis R. Salahub. (2021). Global optimization of ~ 1 nm MoS2 and CaCO3 nanoparticles. Theoretical Chemistry Accounts. 140(4). 4 indexed citations
15.
Tchagang, Alain, François Fauteux, Dan Tulpan, & Youlian Pan. (2017). Bioinformatics identification of new targets for improving low temperature stress tolerance in spring and winter wheat. BMC Bioinformatics. 18(1). 174–174. 9 indexed citations
16.
Tulpan, Dan, Serge Léger, Alain Tchagang, & Youlian Pan. (2015). Enrichment of Triticum aestivum gene annotations using ortholog cliques and gene ontologies in other plants. BMC Genomics. 16(1). 299–299. 10 indexed citations
17.
Tchagang, Alain, Fazel Famili, Heather L. Shearer, et al.. (2012). Mining biological information from 3D short time-series gene expression data: the OPTricluster algorithm. BMC Bioinformatics. 13(1). 54–54. 30 indexed citations
18.
Tchagang, Alain, et al.. (2010). GOAL: A software tool for assessing biological significance of genes groups. BMC Bioinformatics. 11(1). 229–229. 22 indexed citations
19.
Tchagang, Alain, et al.. (2009). Extracting biologically significant patterns from short time series gene expression data. BMC Bioinformatics. 10(1). 255–255. 13 indexed citations
20.
Tchagang, Alain, Ahmed H. Tewfik, Amy P.N. Skubitz, & Keith M. Skubitz. (2006). A differential biclustering algorithm for comparative analysis of gene expression. European Signal Processing Conference. 1–4. 1 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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