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プロフィール詳細
プロジェクトを作成
★★★★★
☆☆☆☆☆
Dr. Ali K.に依頼
Egypt

Machine Learning | Deep Learning | NLP | Bioinformatics | Metagenomics | Drug Repurposing | Systems Biology

プロフィール概要
専門分野
サービス
Data & AI Predictive Modeling, Image Analysis, Data Visualization, Big Data Analytics, Text Mining & Analytics, Data Mining, Data Cleaning, Data Insights
職務経験

PhD Student

University of Luxembourg

3月 2020 - 現在

University of Luxembourg

PhD Researcher

3月 2020 - 2月 2024

Bioinformatics Research Assistant

Nile University

10月 2017 - 9月 2019

Bioinformatics Researcher

H3ABioNet, NIH

1月 2016 - 9月 2017

学歴

Doctorate in Biology

University of Luxembourg

3月 2020 - 2月 2024

Master of Science in Information & Communication: Informatics (School of Information Technology and Computer Science)

Nile University

10月 2017 - 9月 2019

Bachelor in Pharmaceutical Sciences

Mansoura University Faculty of Pharmacy

9月 2009 - 9月 2014

認定資格
  • Single cell data analysis

    University of Luxembourg

    6月 2022 - 7月 2022

出版物
JOURNAL ARTICLE
Luca Di Leo, Chiara Pagliuca, Ali Kishk, Salvatore Rizza, Christina Tsiavou, Chiara Pecorari, Christina Dahl, Maria Pires Pacheco, Rikke Tholstrup, Jonathan Richard Brewer, et al. (2024). AMBRA1 levels predict resistance to MAPK inhibitors in melanoma . Proceedings of the National Academy of Sciences.
Ali Kishk, Maria Pires Pacheco, Tony Heurtaux, Thomas Sauter (2024). Metabolic models predict fotemustine and the combination of eflornithine/rifamycin and adapalene/cannabidiol for the treatment of gliomas . Briefings in Bioinformatics.
Kishk, A., Pires Pacheco, M., Heurtaux, T., Sauter, T.(2024). Metabolic models predict fotemustine and the combination of eflornithine/rifamycin and adapalene/cannabidiol for the treatment of gliomas . Briefings in Bioinformatics. 25. (3).
Di Leo, L., Pagliuca, C., Kishk, A., Rizza, S., Tsiavou, C., Pecorari, C., Dahl, C., Pacheco, M.P., Tholstrup, R., Brewer, J.R., et al.(2024). AMBRA1 levels predict resistance to MAPK inhibitors in melanoma . Proceedings of the National Academy of Sciences of the United States of America. 121. (25).
Tamara Bintener, Maria Pires Pacheco, Demetra Philippidou, Christiane Margue, Ali Kishk, Greta Del Mistro, Luca Di Leo, Maria Moscardó Garcia, Rashi HALDER, Lasse Sinkkonen, et al. (2023). Metabolic modelling-based in silico drug target prediction identifies six novel repurposable drugs for melanoma . Cell Death & Disease.
Bintener, T., Pacheco, M.P., Philippidou, D., Margue, C., Kishk, A., Del Mistro, G., Di Leo, L., Moscardó Garcia, M., Halder, R., Sinkkonen, L., et al.(2023). Metabolic modelling-based in silico drug target prediction identifies six novel repurposable drugs for melanoma . Cell Death and Disease. 14. (7).
Ali Kishk, Maria Pires Pacheco, Tony Heurtaux, Lasse Sinkkonen, Jun Pang, Sabrina Fritah, Simone P. Niclou, Thomas Sauter (2022). Review of Current Human Genome-Scale Metabolic Models for Brain Cancer and Neurodegenerative Diseases . Cells.
Ali Kishk, Maria Pires Pacheco, Tony HEURTAUX, Lasse Sinkkonen, Dr. Jun Pang, Sabrina Fritah, Simone P. Niclou, Thomas Sauter (2022). Review of Current Human Genome-Scale Metabolic Models for Brain Cancer and Neurodegenerative Diseases . Cells.
Claudia Cipriani, Maria Pires Pacheco, Ali Kishk, Maryem Wachich, Daniel Abankwa, Elisabeth Schaffner-Reckinger, Thomas Sauter(2022). Bruceine D Identified as a Drug Candidate against Breast Cancer by a Novel Drug Selection Pipeline and Cell Viability Assay . Pharmaceuticals. 15. (2). Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 179. {MDPI} {AG}
Thomas Sauter, Patricia M. Palagi, Tamara Bintener, Ali Kishk, Luana Presta, Tessy Prohaska, Daniel Guignard, Ni Zeng, Claudia Cipriani, Sundas Arshad, et al. (2022). Project-based learning course on metabolic network modelling in computational systems biology . PLOS Computational Biology.
Claudia Cipriani, Maria Pires Pacheco, Ali Kishk, Maryem Wachich, Daniel Abankwa, Elisabeth Schaffner-Reckinger, Thomas Sauter (2022). Bruceine D Identified as a Drug Candidate against Breast Cancer by a Novel Drug Selection Pipeline and Cell Viability Assay . Pharmaceuticals.
Sauter, T., Bintener, T., Kishk, A., Presta, L., Prohaska, T., Guignard, D., Zeng, N., Cipriani, C., Arshad, S., Pfau, T., et al.(2022). Project-based learning course on metabolic network modelling in computational systems biology . PLoS Computational Biology. 18. (1).
Cipriani, C., Pacheco, M.P., Kishk, A., Wachich, M., Abankwa, D., Schaffner-Reckinger, E., Sauter, T.(2022). Bruceine D Identified as a Drug Candidate against Breast Cancer by a Novel Drug Selection Pipeline and Cell Viability Assay . Pharmaceuticals. 15. (2).
Kishk, A., Pacheco, M.P., Heurtaux, T., Sinkkonen, L., Pang, J., Fritah, S., Niclou, S.P., Sauter, T.(2022). Review of Current Human Genome-Scale Metabolic Models for Brain Cancer and Neurodegenerative Diseases . Cells. 11. (16).
Judit Kumuthini, as members of the Sustainability and Outreach Work Package of the H3ABioNet Consortium, Lyndon Zass, Sumir Panji, Samson P. Salifu, Jonathan K. Kayondo, Victoria Nembaware, Mamana Mbiyavanga, Ajayi Olabode, Ali Kishk, et al. (2019). The H3ABioNet helpdesk: an online bioinformatics resource, enhancing Africa’s capacity for genomics research . BMC Bioinformatics.
Toraih, E.A., Hussein, M.H., Ibrahim, A., AbdAllah, N.B., Mohammed, E.A., Kishk, A.M., Fawzy, M.S.(2019). Beta<sub>2</sub>-adrenergic receptor variants in children and adolescents with bronchial asthma . Frontiers in Bioscience - Elite. 11. (1). Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 61-78.
Kumuthini, J., Zass, L., Panji, S., Salifu, S.P., Kayondo, J.K., Nembaware, V., Mbiyavanga, M., Olabode, A., Kishk, A., Wells, G., et al.(2019). The H3ABioNet helpdesk: An online bioinformatics resource, enhancing Africa's capacity for genomics research . BMC Bioinformatics. 20. (1).
Ghouila, A., Siwo, G.H., Entfellner, J.-B.D., Panji, S., Button-Simons, K.A., Davis, S.Z., Fadlelmola, F.M., Ferdig, M.T., Mulder, N., Bensellak, T., et al.(2018). Hackathons as a means of accelerating scientific discoveries and knowledge transfer . Genome Research. 28. (5). Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 759-765.
BOOK CHAPTER
Bintener, T., Pacheco, M.P., Kishk, A., Didier, J., Sauter, T.(2022). Drug Target Prediction Using Context-Specific Metabolic Models Reconstructed from rFASTCORMICS . Methods in Molecular Biology. 2535. Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 221-240.
CONFERENCE PAPER
Kishk, A., El-Hadidi, M.(2019). AmpliconNet: Sequence Based Multi-layer Perceptron for Amplicon Read Classification Using Real-time Data Augmentation . Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018. Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 2413-2418.
Bakry, U., Fares, M., Kishk, A., El-Hadidi, M.(2019). MetaFlow: An interactive user-friendly workflow for automated analysis of whole genome shotgun sequencing metagenomic data . Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018. Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 2741-2743.
Kishk, A., Elzizy, A., Galal, D., Razek, E.A., Fawzy, E., Ahmed, G., Gawish, M., Hamad, S., El-Hadidi, M.(2018). A Hybrid Machine Learning Approach for the Phenotypic Classification of Metagenomic Colon Cancer Reads Based on Kmer Frequency and Biomarker Profiling . 2018 9th Cairo International Biomedical Engineering Conference, CIBEC 2018 - Proceedings. Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 118-121.