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Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
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Mining Public Databases for Precision Oncology.

Jason Roszik1, Vivek Subbiah2

  • 1Department of Melanoma Medical Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030, USA; Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030, USA.

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Summary
This summary is machine-generated.

Public databases hold valuable data, but it remains siloed. Integrating this information is crucial for advancing precision oncology and delivering personalized treatments effectively.

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Area of Science:

  • Bioinformatics
  • Genomics
  • Clinical Informatics

Background:

  • Significant investment has been made in developing public biological and clinical databases.
  • Current data accessibility is hindered by data residing in isolated, non-interoperable systems ('data silos').

Purpose of the Study:

  • To highlight the challenge of data fragmentation in public databases.
  • To emphasize the necessity of data integration for the advancement of precision oncology.

Main Methods:

  • This study is a perspective piece, analyzing the current state of public data repositories.
  • It reviews the implications of data silos on clinical applications.

Main Results:

  • Public databases, despite substantial funding, are not effectively integrated.
  • Data fragmentation poses a significant barrier to realizing the full potential of precision medicine.

Conclusions:

  • Effective data sharing and integration strategies are essential for precision oncology.
  • Timely access to comprehensive patient and research data at the clinic is critical for optimal treatment decisions.