Profil

Debit Ahmed

Main Referenced Co-authors
Bours, Vincent  (7)
Josse, Claire  (7)
Poulet, Christophe  (6)
Jerusalem, Guy  (5)
Van Steen, Kristel  (4)
Main Referenced Keywords
random forest (5); biomarker signature (4); RNA-seq (4); Cancer Diagnosis (3); Random Forest (3);
Main Referenced Unit & Research Centers
GIGA‐R - Giga‐Research - ULiège [BE] (5)
Human Genetics GIGA-R (4)
BIO3 Unit, Human Genetics GIGA-R (1)
Human Genetics, BIO3 GIGA-R (1)
Human Genetics, BIO3 GIGA-R Uliege (1)
Main Referenced Disciplines
Engineering, computing & technology: Multidisciplinary, general & others (8)
Life sciences: Multidisciplinary, general & others (5)
Computer science (4)
Oncology (2)

Publications (total 16)

The most downloaded
476 downloads
Debit, A. (2014). Detection d'objets rares au sein de coupes histologiques par apprentissage automatique [Master’s dissertation, ULiège - Université de Liège]. ORBi-University of Liège. https://orbi.uliege.be/handle/2268/210158 https://hdl.handle.net/2268/210158

The most cited

7 citations (Scopus®)

Uyisenga, J. P.* , Debit, A.* , Poulet, C., Frères, P., Poncin, A., Thiry, J., Mutesa, L., Jerusalem, G., Bours, V.* , & JOSSE, C.*. (03 June 2021). Differences in plasma microRNA content impair microRNA-based signature for breast cancer diagnosis in cohorts recruited from heterogeneous environmental sites. Scientific Reports, 11 (1), 11698. doi:10.1038/s41598-021-91278-0 https://hdl.handle.net/2268/262168

Poulet, C.* , Debit, A.* , Josse, C., Jerusalem, G., Azencott, C.-A., Bours, V., & Van Steen, K. (2023). Assessing Random Forest self-reproducibility for optimal short biomarker signature discovery. ORBi-University of Liège. https://orbi.uliege.be/handle/2268/303314. doi:10.1101/2023.03.29.534695
* These authors have contributed equally to this work.

Uyisenga, J. P.* , Debit, A.* , Poulet, C., Frères, P., Poncin, A., Thiry, J., Mutesa, L., Jerusalem, G., Bours, V.* , & JOSSE, C.*. (03 June 2021). Differences in plasma microRNA content impair microRNA-based signature for breast cancer diagnosis in cohorts recruited from heterogeneous environmental sites. Scientific Reports, 11 (1), 11698. doi:10.1038/s41598-021-91278-0
Peer Reviewed verified by ORBi
* These authors have contributed equally to this work.

Debit, A. (2020). An in-depth study of random forests methodologies for short biomarker signature discovery [Doctoral thesis, ULiège - Université de Liège]. ORBi-University of Liège. https://orbi.uliege.be/handle/2268/249891

Uyisenga, J., Butera, Y., Debit, A., JOSSE, C., Ainhoa, C. C., Karinganire, E., Cyuzuzo, A. P., Umurungi, N., Kalinijabo, Y., Uwimana, S., Mutesa, L., & Bours, V. (2020). Prevalence of Histological Characteristics of Breast Cancer in Rwanda in Relation to Age and Tumor Stages. Hormones and Cancer. doi:10.1007/s12672-020-00393-3
Peer reviewed

Debit, A. (14 October 2019). Towards an accurate cancer diagnosis modelization: Comparison of random forest strategies [Paper presentation]. IGES 28th Annual Meeting, October 12-14, 2019, Houston, TX, USA, Houston, TX, United States.

Debit, A., Poulet, C., JOSSE, C., Azencott, C.-A., Jerusalem, G., Van Steen, K., & BOURS, V. (15 March 2019). TOWARDS AN ACCURATE CANCER DIAGNOSIS MODELIZATION:COMPARISON OF RANDOM FOREST STRATEGIES [Poster presentation]. 19th BeSHG meeting 15th March 2019 Liege, Belgium, Liege, Belgium.

Debit, A. (2019). Omics signature detection for improved diagnostics [Paper presentation]. Scientific Advisory Board SAB Evaluation, Thematic Unit of Medical Genomics, Liege, Belgium.

Debit, A., & Poulet, C. (2018). Towards an accurate cancer diagnosis modelization: Comparison of Random Forest strategies [Paper presentation]. GIGA-Cancer Seminars, Liege, Belgium.

Debit, A. (2018). Random Forest strategies for cancer diagnosis [Paper presentation]. GIGA Cancer Seminars, Liege, Belgium.

Debit, A. (2018). Towards an accurate cancer diagnosis modelization:Comparison of Random Forest strategies [Paper presentation]. ByteMal 2018, Liege, Belgium.

Debit, A., Poulet, C., JOSSE, C., Van Steen, K., JERUSALEM, G., Bours, V., & Azencott, C.-A. (05 October 2018). Towards an accurate cancer diagnosis modelization: Comparison of Random Forest strategies [Poster presentation]. 5th conference Bioinformatics for young international researchers expo byteMAL 2018, Liege, Belgium.

Debit, A., JOSSE, C., JERUSALEM, G., BOURS, V., & Poulet, C. (13 September 2018). Towards an accurate cancer diagnosis modelization:Comparison of Random Forest strategies [Poster presentation]. JOINT MEETING GIGA-CANCER DAY 2018 / EDT-CANCEROLOGY, Liege, Belgium.

Debit, A. (2018). Algorithm optimization for signature discovery: case of Breast Cancers [Paper presentation]. Unit of Human Genetics - Oncology unit (GIGA) meeting, Liege, Belgium.

Debit, A. (2017). From quality control to normalization of RNA-seq data [Paper presentation]. GIGA-BIO training session, Liege, Belgium.

Debit, A., Wenric, S., JOSSE, C., Van Steen, K., & Bours, V. (May 2017). Normalization and correction for batch effects via RUV for RNA-seq data: practical implications for Breast Cancer Research [Poster presentation]. European Human Genetics Conference ESHG 2017, Copenhagen, Denmark.

Debit, A. (2014). Detection d'objets rares au sein de coupes histologiques par apprentissage automatique [Master’s dissertation, ULiège - Université de Liège]. ORBi-University of Liège. https://orbi.uliege.be/handle/2268/210158

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