Data Science Services

The mission of CTSI Data Science is to coordinate, integrate, streamline, educate, train and support the use of state-of-the-art data science methods in clinical and translational research (or biomedical research) to improve the rigor and reproducibility of research using big data.

The aim of CTSI Data Science is to build bridges across disciplines and coordinate resources by offering consultation and fostering collaboration on research using big data. Our goal is to provide high-quality data science services to investigators, trainees and community organizations at each stage of a study’s lifecycle, including the formulation of research questions, study design, comprehensive data integration, generation of analytic-ready datasets, analytics using state-of-the-art data science methods and other emerging data-driven and data-intense endeavors, and scientific interpretation and reporting.

To achieve this aim, CTSI Data Science works closely with the Center for Biomedical Informatics, the Data Science Institute, Mellowes Center, CTSI Community Engagement, Training and Education programs, CTSI partner institutions, and Community Organizations addressing health and health equity.

For consultation, please contact Naziha Chabir Ferjani at nchabirferjani@mcw.edu to schedule an in-person or virtual appointment. Appointments may be scheduled at least 24 hours prior to the actual time of appointment.

Services

Data Science services are tailored to the needs of investigators and range from one time consultation, routine service support to short- or long-term collaboration to enhance the research efforts of investigators and trainees. Service types include, but are not limited to:

Development or review of research plan or grant proposals

Provide expert guidance on the formulation or refining of research questions
Coordinate and help investigators and trainees to identify appropriate resources, including quantitative resources on campus and publicly available datasets and data science tools
Facilitate data acquisition, database development and the generation of comprehensive databases through the integration of different data sources
Provide expert guidance on efficient and rigorous study design, sample size and power analyses
Support for developing analysis plan
Review of gran proposals

Data Analysis support

Data preprocessing and generation of analysis-ready datasets
Support for data integration and integrative analyses
Appropriate rigorous and reproducible analyses of big data using machine learning/artificial intelligence and other emerging data-driven and data-intense methods for biomedical data mining and risk/outcome prediction
Analyses of unstructured health data

Publication development and review

Data visualization: Prepare high quality tables and figures for scientific meetings and papers
Support for results interpretation, writing of the methods, results and discussion sections of abstracts and manuscripts
Review of manuscripts

Other

Collaborate with CTSI partners to develop data science analytical tools/pipelines/software
To educate individuals and teams on data science concepts and tools through seminars, workshops and individual sessions to enhance the analytical competencies of investigators and trainees.
You can also contact us with all other research design and analysis questions related to the use of big data.
Data Science Fellowship: A six-month collaboration with a CTSI faculty who will provide formal training and mentorship for investigators to incorporate data science in their own project and help advance investigator’s knowledge in data science
Collaboration with clinical investigators to provide clinical education to data scientists and informatics teams

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