Anne Deslattes Mays, Ph.D.
Principal Computational ScientistThe Jackson Laboratory
Dr. Anne Deslattes Mays is a computational scientist driven to conquer challenges in complex systems biology–oriented datasets. She holds a PhD in Tumor Biology, M.Sc. in Computer Science and a B.Sc. in Mathematics. From air-traffic control modeling and simulation to sequencing the human genome, she has been at the forefront of envisioning solutions to large-scale problems. Her role in starting the Software Sequencing group at Celera genomics was to break down the problem of managing large-scale sequencing data into a pipeline, and staff the parts of the developing of the pipeline, in such a way that the job could be accomplished by non-biology-exposed software engineers. As Director of Applied Systems Biology at Keygene, she oversaw a team of scientists that used transcriptomic approaches to discover novel plant traits that facilitate adaptation to biotic and abiotic stressors. This work led to the identification of three novel genetic targets for improving drought resistance and patents for each of these targets. She was one of the first users of Transcript of Full Length Unassembled, now known as ISO-seq. She used this algorithm and the PacBio ISO-seq data to segregate lineage-negative cell populations from progenitor-positive cells in healthy human bone marrow. She has been described as a very energetic, entrepreneurial computer scientist, on the one hand capable of creating and initiating new ideas and scientific concepts and on the other hand also capable of implementing them and making these work.
As Principal Computational Scientist at The Jackson Laboratory, she is tasked with setting up data services. Focused on ensuring that data adhere to the dictates of findability, accessibility, interoperability and reusability (FAIR) while adhering to the W3C standards ensuring that data are described with unique and persistent identifiers at the individual level (ORCID), to the institutional level (RRID), and describing these data in triples of subject, predicate and object, representing their relationships in resource description frameworks. Data Services entails data collection, data processing and data delivery. Data collection begins at data generation from each of the scientific services. Data are archived at the point of data generation with metadata, ensuring the ability to perform derivative data processing now and for the future. Knowledge of the measurement technologies, compute infrastructure and the biological domain allow me to continue to apply my nearly 20 years of genomics experience to create the appropriate data architecture that will support not only internal but also be able to interoperate with external data. This work moves from one principal investigator to an institutional-wide to a world-wide service capability.