Stanford University
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Derek Mendez
Staff Scientist, SLAC National Accelerator Laboratory
Current Role at StanfordComputational staff scientist at the Stanford Synchrotron Radiation Lightsource (SSRL), in the Macromolecular Crystallography group (Structural and Molecular Biology division).
Main activities revolve around a 3 year BRaVE-funded project to build a new X-ray resource for the acceleration of medicines development (XMeD). Active in-silico areas of research are in the characterization of crystallization outcomes, virtual and experimental screening of ligands, in-silico methods for lead molecule optimization, and extremely sensitive absorption profile characterization using machine learning techniques. A major computational goal is to determine the most valuable tools (and develop new ones) for future XMeD users.
Beyond XMeD, we are focusing on using GPUs and machine learning models to accelerate processing and characterization of user diffraction data that is collected at SSRL beamlines 12-1, 12-2, 14-1, and 9-2. In addition, we are aiming to make available to users new methods that process X-ray diffraction data at the pixel-level in order to extract more information to better resolve structural changes in proteins arising from e.g., binding events and light/chemical driven dynamics.
We are also partnering with NERSC to build a framework for our beamline users to offload computationally intensive jobs to the Perlmutter GPU cluster. -
Hector Mendez
Postdoctoral Scholar, Cardiovascular Medicine
BioDr. Hector Rodrigo Mendez is a Medical Geneticist from Argentina. Rodrigo completed a residency program in Medical Genetics at Centro Nacional de Genetica Medica – ANLIS (Buenos Aires, Argentina) and a Master’s program in Medical Molecular Biology at Buenos Aires University.
Rodrigo continued his scientific career at a German Genomic Start-up, working as a human geneticist and providing his experience in rare disorders, genomic data (WGS/WES/gene panels) analysis, variant interpretation, and its integration with a deep focus on genotype-phenotype correlation.
Rodrigo’s areas of expertise are rare disorders, NGS technology, Whole Genome Sequencing analysis, and ACMG interpretation guidelines, and his research aims are:
- Collection and analysis of clinical data through deep-learning phenotyping approaches.
- Multi-omic data integration to elucidate complex and rare genetic disorders.
- Drive progress in curing rare genetic diseases, particularly among critically sick infants.
At Stanford University, under the supervision of Dr. Matthew Wheeler, he is conducting his postdoctoral research studies to achieve his scientific goals.
