Influential Women spotlights NCATS computational biology fellow Soukaina Amniouel

Influential Women has profiled Soukaina Amniouel, PhD, a postdoctoral fellow at NCATS whose work combines bioinformatics and machine learning to support cancer, neurological and rare disease research. The profile highlights her translational medicine focus, mentoring role at George Mason University and the growing push to turn complex biological data into clinical insight. Why it matters: - Soukaina Amniouel’s work sits at the intersection of AI, bioinformatics and translational science, a combination that can speed up personalized medicine and improve therapeutic decisions. - Her research spans cancer, neurological disorders and rare diseases, where better data analysis can help move scientific findings closer to patient care. - The profile reflects the growing demand for computational tools that can make large biological datasets useful in clinical discovery. What happened: - Influential Women published a profile of Soukaina Amniouel, PhD, a postdoctoral fellow in computational biology at the National Center for Advancing Translational Sciences, on June 12, 2026. - Amniouel works at NCATS on bioinformatics and AI/ML-driven research aimed at advancing studies in cancer, neurological disorders and rare diseases. - The profile also notes that Amniouel serves as an adjunct faculty instructor at George Mason University. - The profile includes a connect page for Soukaina Amniouel . The details: - Amniouel originally trained in molecular biology in Morocco before moving into bioinformatics. - Her PhD in Bioinformatics and Computational Biology came from George Mason University. - During doctoral research, Amniouel built machine learning models to analyze gene expression data and predict chemotherapy efficacy. - Her technical background includes predictive modeling, algorithm development and large-scale biological data analysis. - Her research has included neuroinflammatory pathways tied to Alzheimer’s disease and studies of rare genetic conditions. - Amniouel has presented at national and international conferences and contributed to peer-reviewed publications. - She has also secured NIH/NCATS funding for innovative studies. - At George Mason University, she teaches cell biology, biostatistics and medical microbiology. - She supports women entering STEM through mentorship and education. Between the lines: - The profile frames Amniouel as part of a broader shift toward researchers who can move between wet-lab biology, computational methods and clinical applications. - Her emphasis on networking and mentorship suggests that technical skill alone is not enough in a competitive research field. - Her focus on collaboration and clinical relevance shows the pressure on computational scientists to produce work that can be translated into outcomes that matter for patients. - The profile presents AI as one of the clearest growth areas for cancer research, drug discovery and rare disease treatment development. What’s next: - Amniouel is likely to keep expanding her work in multi-omics, machine learning and translational research. - Her profile points to continued efforts to connect computational findings with clinical impact across multiple disease areas. - She also plans to continue mentoring and teaching emerging scientists, especially women in STEM. The bottom line: - Soukaina Amniouel’s profile spotlights a researcher using computational biology to turn complex data into more actionable science for patients with hard-to-treat diseases.