Mohieddin Jafari earned a Ph.D. in Applied Proteomics in 2013 from the Beheshti University of Medical Sciences under the supervision of Professor Mehdi Sadeghi. During his predoctoral studies (2011) at the Proteomics Resource at the Harvard School of Public Health (HSPH), he concentrated on protein fractionation in mass spectrometry-based proteome profiling under the supervision of Professor Alexander Ivanov. In 2015, he graduated from the Systems Biology Specialization Certificate program at the Icahn School of Medicine at Mount Sinai, where he focused on network biology applications employing high-throughput data mining and network analysis tools. In 2018, he began working as a senior researcher at the University of Helsinki, following 1+3 years as a postdoc and PI at the Pasteur Institute of Iran. He began his career at FIMM for one year before joining the ONCOSYS Research Program Unit, Dept. of Pharmacology, and Clinical Proteomics Core Facility, for more than three years. In 2020, he obtained his Docentship in Bioinformatics from Helsinki University. In 2023, Dr. Jafari launched his independent career as a principal investigator (PI) in the Systems Pharmacology Research Group, Department of Biochemistry and Developmental Biology.
Mohieddin believes that research should be a lot of fun! That means digging into cool experiments in a laid-back work environment. When it comes to crunch time, we buckle down, but we also believe in maintaining a healthy work-life balance. Every member of the team is crucial, and we're on a mission to learn something new every day!
tel: +358 40 545 8989
Elham is a doctoral researcher whose main focus is on exploring protein–drug, protein–metabolite, and protein-protein interactions. She received her BSc degree in cellular and molecular biology, completed her M.Sc. in clinical biochemistry at Semnan University of Medical Sciences in 2020, and joined Dr. Jafari’s research group in 2021 to pursue her PhD. During her master's, she focused on drug target interaction and mechanism of action identification using a high-throughput proteomic technique. Currently, she is developing this proteomic technique into combination therapy for acute myeloid leukemia.
Research interests: cancer research, molecular systems biology, proteomics, mass spectrometry, bioinformatics, and drug combination analysis.
Ehsan Zangene successfully attained his Ph.D. in Bioinformatics in 2023, specializing in Cancer Synthetic Lethality (SL) pair prediction at the University of Tehran in Iran. His doctoral research introduced an innovative pipeline for predicting metabolic SL pairs through constraint-based modeling of metabolism, making a substantial contribution to the field. Since 2017, Ehsan has been actively engaged in disseminating knowledge within the domains of bioinformatics, systems biology, and metabolic modeling. He established the BioUT channel on Telegram and Instagram, where he conducted workshops to educate and engage individuals interested in these subjects. Ehsan's dedication to education extended to teaching bioinformatics to master's students at both Tehran University of Medical Sciences and Shahed University. Furthermore, he has a solid presence in web application development, data visualization, and scientific illustration, simplifying intricate concepts and making them more accessible to a broader audience. In 2023, Ehsan embarked on a new chapter by relocating to Finland to undertake a postdoctoral researcher role at the University of Helsinki. His work focuses on drug combination prediction within the computational and experimental domains, contributing to advancements in this critical area of research.
Rashwita Gyanwali, MSc
Rashwita, a former summer intern in my lab, made contributions to projects related to drug response analysis and protein-based experiments, further enhancing her understanding of computational models in research.
Mehdi Mirzaie, Ph.D.
Mehdi, a former Senior Postdoctoral Researcher in my lab, played a key role in advancing our research on drug combination prediction, showcasing his expertise in computational models within the field.