HitWalker2

Visual analytics for precision medicine and beyond

Daniel Bottomly, Shannon McWeeney, Beth Wilmot

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

The lack of visualization frameworks to guide interpretation and facilitate discovery is a potential bottleneck for precision medicine, systems genetics and other studies. To address this we have developed an interactive, reproducible, web-based prioritization approach that builds on our earlier work. HitWalker2 is highly flexible and can utilize many data types and prioritization methods based upon available data and desired questions, allowing it to be utilized in a diverse range of studies such as cancer, infectious disease and psychiatric disorders.

Original languageEnglish (US)
Pages (from-to)1253-1255
Number of pages3
JournalBioinformatics
Volume32
Issue number8
DOIs
StatePublished - Apr 15 2016

Fingerprint

Visual Analytics
Precision Medicine
Prioritization
Bioelectric potentials
Medicine
Communicable Diseases
Psychiatry
Visualization
Infectious Diseases
Web-based
Disorder
Neoplasms
Cancer
Range of data
Genetics
Framework
Interpretation

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology
  • Computational Theory and Mathematics
  • Computer Science Applications
  • Computational Mathematics
  • Statistics and Probability

Cite this

HitWalker2 : Visual analytics for precision medicine and beyond. / Bottomly, Daniel; McWeeney, Shannon; Wilmot, Beth.

In: Bioinformatics, Vol. 32, No. 8, 15.04.2016, p. 1253-1255.

Research output: Contribution to journalArticle

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