Francesc Lopez-Giraldez

Dr. Francesc Lopez-Giraldez is a Research Scientist in the Department of Genetics at Yale School of Medicine, where he serves as Associate Director of Bioinformatics at the Yale Center for Genome Analysis (YCGA). He is also affiliated with the Genomics, Genetics, and Epigenetics Program at Yale Cancer Center and participates in the Yale-BI Biomedical Data Science Fellowship.

Dr. Lopez-Giraldez received his BS in Biology from University of Girona (2000), MSc in Health and Life Sciences from Pompeu Fabra University (2004), and PhD in Evolutionary Genetics from Autonomous University of Barcelona (2006). He completed postdoctoral training through a Beatriu de Pinós fellowship from Generalitat de Catalunya (2009).

His research spans genomics, bioinformatics, cancer genetics, and evolutionary genetics, with significant contributions to understanding congenital heart disease, immune checkpoint mechanisms, and mTOR signaling pathways. His work bridges computational biology with clinical applications, particularly in cancer genomics and developmental disorders.

Dr. Lopez-Giraldez's publication record shows consistent productivity with numerous papers in high-impact journals including Nature, PNAS, and Journal of Investigative Dermatology. His research demonstrates expertise in genomic analysis, spatial transcriptomics, and molecular mechanisms underlying various diseases.

• National Cancer Institute Research Specialist Award (R50) (2023)

Dr. Lopez-Giraldez has mentored students at various levels, including high school and graduate students. As Associate Director of Bioinformatics at YCGA, he oversees bioinformatics infrastructure and analysis pipelines that support numerous research projects across Yale. His NCI R50 award provides dedicated support for his specialized research contributions to cancer genomics.

While specific lab details aren't provided in the text, his role as Associate Director of Bioinformatics at YCGA places him at the center of Yale's genomic research infrastructure, providing computational expertise and leadership for large-scale genomic studies across multiple disease areas.