Yanis Zirem

is passionate about life sciences, health, and medical technologies, he specializes in molecular organic and omics analysis to better understand biological systems. Bridging the gap between wet lab and dry lab, his work focuses on connecting benchwork experiments with the data they generate. After a year of experience as a bioinformatics engineer (2022-2023), he is currently in his second year of PhD (2025). His research aims to develop data analysis algorithms, artificial intelligence pipelines, and software for the analysis of mass spectrometry data (1D, 2D, 3D, and multimodal), enabling their full exploitation, result interpretation, and meaningful insights. With a strong background in biochemistry and advanced skills in data science, including hyperspectral image processing and machine learning, he has designed 1D and 2D pipelines to enhance the classification of biological tissue subtypes and cancer grades. These tools not only improve predictive performance but also help identify critical biomarkers. Additionally, he has contributed to the development of immunoscoring and bacterioscoring methods based on mass spectrometry imaging to explore the tumor microenvironment and microbiomes. He has also been involved in establishing the concept of “dry proteomics,” which enables the identification of protein markers for specific regions of interest using lipid imaging, classifies regional profiles, and highlights the biological pathways involved in a theragnostic context. Yanis Zirem is the author of six research articles (five as the first or co-first author) and has developed four software tools for real-time cancer diagnosis and prognosis, biomarker identification, and molecular imaging processing. He has presented his work at numerous national and international conferences, including:
-MSACL 2023 (Monterey, USA, March 2023): Development of Innovative Mass Spectrometry Pipelines for Improved Cancer Diagnosis and Biomarker Identification through Feature Extraction.
-Journée Lipidomystes (Paris, France, November 2023): Real-time analysis of glioblastoma tumor microenvironment using SpiderMass for surgical decision-making and patient prognosis.
-AI in Oncology Symposium (Rouen, France, December 2023): Real-time glioblastoma analyses using SpiderMass.
-EURON PhD Days (Lille, France, February 2024): Real-time diagnosis and prognosis of glioblastoma with SpiderMass technology.
-EMIM 2024 (Porto, Portugal, March 2024): AI pipelines for tumor microenvironment analysis of glioblastoma using SpiderMass.
-MSACL 2024 (Monterey, USA, March 2024): Advancing ambient mass spectrometry with machine learning integration.
-IMSC 2024 (Melbourne, Australia, August 2024): Multi-omics integration informed by SVD k-means++ clustering for dry proteomics guided by lipid MALDI-MSI.
He has also contributed posters to prestigious conferences, such as ASMS 2024 (Anaheim, USA) and EuBIC-MS Winter School 2024 (Winterberg, Germany).

Beyond his research, Yanis has mentored five students (two undergraduate, two Master’s 1, and one Master’s 2) during their internships. He is actively involved in peer review for journals like Scientific Reports, Bio-Protocol, Journal of Investigative Dermatology, and Analytical Chemistry.