No-boundary thinking in bioinformatics research

Xiuzhen Huang, Barry Bruce, Alison Buchan, Clare Bates Congdon, Carole L. Cramer, Steven F. Jennings, Hongmei Jiang, Zenglu Li, Gail McClure, Rick McMullen, Jason H. Moore, Bindu Nanduri, Joan Peckham, Andy Perkins, Shawn W. Polson, Bhanu Rekepalli, Saeed Salem, Jennifer Specker, Donald Wunsch, Donghai XiongShuzhong Zhang, Zhongming Zhao

Research output: Contribution to journalReview articlepeer-review

10 Scopus citations


Currently there are definitions from many agencies and research societies defining "bioinformatics" as deriving knowledge from computational analysis of large volumes of biological and biomedical data. Should this be the bioinformatics research focus? We will discuss this issue in this review article. We would like to promote the idea of supporting human-infrastructure (HI) with no-boundary thinking (NT) in bioinformatics (HINT).

Original languageEnglish (US)
Article number19
JournalBioData Mining
Issue number1
StatePublished - 2013

Bibliographical note

Funding Information:
With the rapid advance of biotechnologies and development of clinical record systems, we have witnessed an exponential growth of data ranging from “omics” (such as genomics, proteomics, metabolomics, and pharmacogenomics), imaging data, to electronic medical record data. Last year, the federal funding agencies National Institutes of Health (NIH) and National Science Foundation (NSF) exercised a joint effort to launch big-data initiatives and consortia to promote and support big-data projects [2]. Focused specifically on computational medicine and personalized treatments, large consortia have been initiated (such as The Cancer Genome Atlas (TCGA); to collect large quantities of data and conduct analyses with the hope of addressing cancer causes, diagnosis, prognosis, and treatments.

Funding Information:
Supported by NSF EPSCoR Grant Number #1239812.


  • Human infrastructure
  • No-boundary thinking


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