Search

The Modified Checklist for Autism in Toddlers, Revised, with Follow-up (M-CHAT-R/F) is a questionnaire used widely by health professionals to identify toddlers at risk for Autism Spectrum Disorder (ASD). This poster describes how Prometheus Research developed a secure, standalone, web-based version of the questionnaire and scoring algorithm that allows 1) parents to complete the form at home or at the doctor’s office; 2) doctors to review the results, discuss them with the parent, and follow-up on those with increased risk for developing ASD; and 3) researchers to aggregate the results across 10+ clinics. Find out more about RexDB at http://www.rexdb.org, or download the source code at http://www.bitbucket.org/rexdb.

Understanding the scope of research activities in a scientific community requires leveraging data from multiple public and private sources. However, data from different sources, such as PubMed and NIH RePORTER, may be difficult to link because data are organized differently, are of inconsistent or poor quality or lack appropriate identifiers. The standard solution to these challenges is to use an Extract, Transform and Load process (ETL), which pulls the data out of the original data source, changes its structure and content, then stores it in the target database. However, ETL processes tend to be brittle, expensive, and difficult to run. We needed a data-integration solution that would remain flexible and inexpensive, and would support an expanding list of ad hoc data sources to support decisions about scientific funding.

Making decisions about scientific direction, such as funding of research programs, requires a variety of information sources. Science officers require knowledge of multiple internal sources about grants, as well as multiple external sources about grants and publications. Access to a wide range of systems can increase costs and reduce the speed of decisions. Different kinds of tasks (use cases) often result in very different software solutions, such as customized “dashboards”. These attempts usually fail due to long delivery times, measured in months or years. By the time the dashboard is delivered, decisions and data have changed. Our approach is to produce a platform for rapidly configuring decision support dashboards that can be delivered in a matter of days or hours.

We compare the efficiency of (1) just-in-time data management, in which data are cleaned prior to each analysis, and (2) integrated data management, in which data are centralized, cleaned up front, and made available via a query interface. Integrated data management was associated with faster completion of data management requests.

We produced a platform for rapidly configuring decision support dashboards that can be delivered in days or hours. The platform was created using an agile methodology over 10 weekly iterations. We developed a data warehouse for storing data about scientific research, added a web-native data-access layer (HTSQL) and a rapid web-application framework (HTRAF). The prototype was developed in two weeks and included a total of 21 different screens covering 5 use cases for usability reviews. The final tool contained 191,000 total records from multiple internal and external grants and publications sources. Specifically, the application included 136,000 NIH records and 39,800 PubMed Publications, 7,800 scientists across 1,300 institutions and 2,400 internal records.

Biology is perhaps the most complex of the sciences, given the incredible variety of chemical species that are interconnected in spatial and temporal pathways that are daunting to understand. Their interconnections lead to emergent properties such as memory, consciousness, and recognition of self and non-self. To understand how these interconnected reactions lead to cellular life characterized by activation, inhibition, regulation, homeostasis, and adaptation, computational analyses and simulations are essential, a fact recognized by the biological communities. At the same time, students struggle to understand and apply binding and kinetic analyses for the simplest reactions such as the irreversible first-order conversion of a single reactant to a product. This likely results from cognitive difficulties in combining structural, chemical, mathematical, and textual descriptions of binding and catalytic reactions. To help students better understand dynamic reactions and their analyses, we have introduced two kinds of interactive graphs and simulations into the online educational resource, Fundamentals of Biochemistry, a multivolume biochemistry textbook that is part of the LibreText collection. One type is available for simple binding and kinetic reactions. The other displays progress curves (concentrations vs time) for both simple reactions and more complex metabolic and signal transduction pathways, including those available through databases using systems biology markup language (SBML) files. Users can move sliders to change dissociation and kinetic constants as well as initial concentrations and see instantaneous changes in the graphs. They can also export data into a spreadsheet for further processing, such as producing derivative Lineweaver-Burk and traditional Michaelis-Menten graphs of initial velocity (v0) vs substrate concentration.