Optimized and secure databases for complex data and metadata. Expressive querying to search, slice, and merge, across data types.
Execution of arbitrarily complex custom workflows. Third-party algorithm incorporation. Automated parallelization for execution on cloud infrastructure. Exact record of computed analyses.
Genomics Technology, Data Management & Analysis; Ontologies & Robust Data Models; Petabyte-Scale Data Computation & High-Performance Computing.
Advances in genomic technology have made it easier to generate sequence data to address problems in medicine and biological research. Solvuu develops software for basic, translational, and clinical genomics that empowers scientists to think in terms of data (avoiding custom scripting).
Users can import large datasets and flexibly manage them with custom schemas. We build databases and query languages that enable a uniform view of genomics data/metadata types, optimize storage efficiency, and securely store personally identifiable data. Our query languages have a formally defined syntax and semantics, and empower researchers to flexibly search, slice, and merge data across data types and repositories.
Users can define arbitrarily complex workflows with popular 3rd party genomics tools. Our software automatically parallelizes and executes custom operations on a distributed compute infrastructure. It also provides an exact record of computed analyses to support scientific reproducibility.
Solvuu's team has built genomics laboratory information and data management systems that include: web interfaces with authentication; data visualizations; integrated databases that store millions of files and track complex metadata; command-line tools for end-users; and workflows that launch and track jobs on high-performance computing infrastructure.
Solvuu was founded by Ashish Agarwal (firstname.lastname@example.org) and Paul Scheid (email@example.com) and is currently in development mode.
Ashish led bioinformatics and software engineering initiatives for the Genomics Core at NYU's Center for Genomics and Systems Biology and was Research Faculty in Yale University’s Computer Science Department. He completed a Postdoctoral Fellowship in Bioinformatics at Yale and a PhD in programming language theory at Carnegie Mellon University.
Paul managed the Genomics Core at NYU's Center for Genomics and Systems Biology. In this capacity, he consulted with investigators to design and execute next-generation sequencing projects; supervised core technical staff; and oversaw next-generation sequencing operations and data-quality assessment. In addition, Paul has overseen several experimental design efforts in large scale genomics consortia.