Nanoinformatics for environmental health and biomedicine

• Rong Liu and
• Yoram Cohen

Beilstein J. Nanotechnol. 2015, 6, 2449–2451, doi:10.3762/bjnano.6.253

• implementing effective mechanisms for collecting, validating, storing, sharing, analyzing, modeling, and applying that information.” [1]. At present, nanoinformatics focuses primarily on: nano-data management and database development, nano-data curation, assessment of the value of information in nano-data

• analysis techniques (e.g., multicriteria decision analysis, value of information, weight of evidence, and portfolio decision analysis) that are potentially capable of assessing and classifying the multitude of available nanomaterial data. Such an approach can serve as the basis for both establich a

How decision analysis can further nanoinformatics

• Matthew E. Bates,
• Sabrina Larkin,
• Jeffrey M. Keisler and
• Igor Linkov

Beilstein J. Nanotechnol. 2015, 6, 1594–1600, doi:10.3762/bjnano.6.162

• techniques of multicriteria decision analysis (MCDA), value of information (VOI), weight of evidence (WOE), and portfolio decision analysis (PDA) can bridge the gap from current data collection and visualization efforts to present information relevant to specific decision needs. Decision analytic and

• Bayesian models could be a natural extension of mechanistic and statistical models for nanoinformatics practitioners to master in solving complex nanotechnology challenges. Keywords: decision analysis; nanoinformatics; policy; portfolio analysis; risk assessment; value of information; weight of evidence

• , we review the use of multicriteria decision analysis (MCDA), value of information (VOI), weight of evidence (WOE), and portfolio decision analysis (PDA) from the perspective of nanoinformatics. We propose that this set of decision analytic methods should be explicitly developed as the next step to