Farida Zehraoui

481 total citations
25 papers, 281 citations indexed

About

Farida Zehraoui is a scholar working on Molecular Biology, Artificial Intelligence and Cancer Research. According to data from OpenAlex, Farida Zehraoui has authored 25 papers receiving a total of 281 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Molecular Biology, 12 papers in Artificial Intelligence and 7 papers in Cancer Research. Recurrent topics in Farida Zehraoui's work include Cancer-related molecular mechanisms research (6 papers), RNA and protein synthesis mechanisms (6 papers) and Gene expression and cancer classification (6 papers). Farida Zehraoui is often cited by papers focused on Cancer-related molecular mechanisms research (6 papers), RNA and protein synthesis mechanisms (6 papers) and Gene expression and cancer classification (6 papers). Farida Zehraoui collaborates with scholars based in France, Algeria and Switzerland. Farida Zehraoui's co-authors include Blaise Hanczar, Fariza Tahi, David Israeli, Laurence Jeanson-Leh, Van Du T. Tran, Sébastien Tempel, Younès Bennani, Abdelhafid Bendahmane, Georges Tarlet and Marc Benderitter and has published in prestigious journals such as Nucleic Acids Research, Bioinformatics and PLoS ONE.

In The Last Decade

Farida Zehraoui

22 papers receiving 273 citations

Peers

Farida Zehraoui

RNMI

Dimitrios Kleftogiannis Saudi Arabia

Euiseong Ko United States

Binhua Tang China

CJ Barberan United States

Antoine Bodein Canada

C. Wolfe United States

Zeina R. Al Sayed France

Jialin Zhang China

Padideh Danaee United States

Le Yang China

Dimitrios Kleftogiannis Saudi Arabia

Farida Zehraoui

404 ×2.1

71 ×1.1

162 ×2.7

30 ×1.2

13 ×0.8

RNMI

Citations per year, relative to Farida Zehraoui Farida Zehraoui (= 1×) peers Dimitrios Kleftogiannis

Countries citing papers authored by Farida Zehraoui

Since Specialization

Citations

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

Fields of papers citing papers by Farida Zehraoui

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Farida Zehraoui

This figure shows the co-authorship network connecting the top 25 collaborators of Farida Zehraoui. A scholar is included among the top collaborators of Farida Zehraoui 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 Farida Zehraoui. Farida Zehraoui 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

Zehraoui, Farida, et al.. (2025). MMnc: multi-modal interpretable representation for non-coding RNA classification and class annotation. Bioinformatics. 41(3).

Angel, Éric, et al.. (2024). Biobjective gradient descent for feature selection on high dimension, low sample size data. PLoS ONE. 19(7). e0305654–e0305654. 2 indexed citations

Zehraoui, Farida, et al.. (2024). Comparison and benchmark of deep learning methods for non-coding RNA classification. PLoS Computational Biology. 20(9). e1012446–e1012446. 3 indexed citations

Vahid, Milad R., et al.. (2023). AttOmics: attention-based architecture for diagnosis and prognosis from omics data. Bioinformatics. 39(Supplement_1). i94–i102. 4 indexed citations

Postic, Guillaume, et al.. (2023). IRSOM2: a web server for predicting bifunctional RNAs. Nucleic Acids Research. 51(W1). W281–W288. 2 indexed citations

Zehraoui, Farida, et al.. (2023). A3SOM, abstained explainable semi-supervised neural network based on self-organizing map. PLoS ONE. 18(5). e0286137–e0286137. 3 indexed citations

Hanczar, Blaise, et al.. (2022). Assessment of deep learning and transfer learning for cancer prediction based on gene expression data. BMC Bioinformatics. 23(1). 262–262. 28 indexed citations

Zehraoui, Farida, et al.. (2022). MS-LSTMEA: Predicting Clinical Events for Hypertension Using Multi-Sources LSTM Explainable Approach. SSRN Electronic Journal. 1 indexed citations

Zehraoui, Farida, et al.. (2022). GraphGONet: a self-explaining neural network encapsulating the Gene Ontology graph for phenotype prediction on gene expression. Bioinformatics. 38(9). 2504–2511. 16 indexed citations

10.

Zehraoui, Farida, et al.. (2021). Deep GONet: self-explainable deep neural network based on Gene Ontology for phenotype prediction from gene expression data. BMC Bioinformatics. 22(S10). 455–455. 23 indexed citations

11.

Hanczar, Blaise, et al.. (2020). Biological interpretation of deep neural network for phenotype prediction based on gene expression. BMC Bioinformatics. 21(1). 501–501. 28 indexed citations

12.

Batouche, Mohamed, et al.. (2019). A Novel Integrative Approach for Non-coding RNA Classification Based on Deep Learning. Current Bioinformatics. 15(4). 338–348. 8 indexed citations

13.

Hanczar, Blaise, et al.. (2018). Phenotypes Prediction from Gene Expression Data with Deep Multilayer Perceptron and Unsupervised Pre-training. International Journal of Bioscience Biochemistry and Bioinformatics. 8(2). 125–131. 7 indexed citations

14.

Zehraoui, Farida, Adnane Boualem, Mohamed Batouche, et al.. (2017). IpiRId: Integrative approach for piRNA prediction using genomic and epigenomic data. PLoS ONE. 12(6). e0179787–e0179787. 15 indexed citations

15.

Tran, Van Du T., et al.. (2015). miRBoost: boosting support vector machines for microRNA precursor classification. RNA. 21(5). 775–785. 31 indexed citations

16.

Heinonen, Markus, Olivier Guipaud, Fabien Milliat, et al.. (2014). Detecting time periods of differential gene expression using Gaussian processes: an application to endothelial cells exposed to radiotherapy dose fraction. Bioinformatics. 31(5). 728–735. 28 indexed citations

17.

Zehraoui, Farida, et al.. (2014). Towards a piRNA prediction using multiple kernel fusion and support vector machine. Bioinformatics. 30(17). i364–i370. 40 indexed citations

18.

Thomas, Sophie, Enas Abdulhay, Pierre Baconnier, et al.. (2007). SAPHIR - a multi-scale, multi-resolution modeling environment targeting blood pressure regulation and fluid homeostasis. Conference proceedings. 281. 6648–6651. 10 indexed citations

19.

Zehraoui, Farida & Younès Bennani. (2005). NEW SELF-ORGANIZING MAPS FOR MULTIVARIATE SEQUENCES PROCESSING. International Journal of Computational Intelligence and Applications. 5(4). 439–456. 4 indexed citations

20.

Zehraoui, Farida & Younès Bennani. (2004). M-SOM-ART: growing self organizing map for sequences clustering and classification. European Conference on Artificial Intelligence. 28(4). 564–568. 5 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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