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Computational Sciences (CS), part of Data Science at The Jackson Laboratory, supports JAX's researchers and collaborators in the application of advanced computational and analytical approaches to complex, data-intensive biological problems; development of scientific software applications that facilitate access, visualization and sharing of data and algorithms with the scientific community; and development of new scientific projects and platforms to arrive at novel, relevant and interesting biological inferences. CS also works with JAX researchers and product managers to design, develop and operate integrative platforms essential for successful delivery of the JAX's research data and service products. In addition, CS provides support for grant applications; project planning & design; data movement & management; and consultation & training in scientific computing, bioinformatics and biostatistics.
This service is only available to faculty and researchers at The Jackson Laboratory.
Two world-leading organizations are partnering to further expand AI capabilities in biomedical science and catalyze medical progress.
Five major lessons learned since sequencing the 1st human genome.
The Gene Expression Database for Mouse Development has been named a Global Core Biodata Resource in the 2023 selection round.
Scientists from JAX are being recognized for their outstanding achievements by the IMGS, a group that fosters research in mammalian genetics, and represents its members in their professional activities.
JAX researchers are at the forefront of developing and implementing AI-based technologies for a variety of research applications.
Paul Robson is leading a JAX team as part of the Human BioMolecular Atlas Program. A new paper in Nature Cell Biology presents the work done to date to establish the program’s frameworks as well as future steps.
Mary Teena Joy investigates what happens to the brain after a stroke and how to enhance brain neural rewiring to improve recovery.
A synopsis of what The Cube Initiative is at JAX and why it may have a marked impact on the bridge between research and clinical application.