Molecular Recognition and Physiological Recognition: A Comprehensive Biometrics Perspective
Traditionally defined, automated biometric recognition is the automatic recognition of individuals through the processing, storage, and comparison of digital records derived from measurable traits which are adequately unique for a given application (i.e. fingerprint, iris, face, DNA). In the late 1990’s WVU developed a unique comprehensive perspective on the area as it organized its NSF Industry University Cooperative Research Center in biometrics. This comprehensive perspective had two critical dimensions. First, that effective treatment of biometrics requires its recognition as a convergence of disciplines requiring an interdisciplinary approach spanning biology, devices, pattern recognition, statistics, and systems as well as societal and legal issues. Second, that the full spectrum of biometric traits extend from the molecular to the physiological. Therefore while near term opportunities for biometrics research are clearly in physiological biometrics, ultimately, high performance multimodal recognition systems will span both physiological and molecular traits and a foothold for addressing what we refer to here as molecular biometrics must be established.
Realization of automated rapid human biometric recognition based on DNA or other molecular signature sets represents a long-term research challenge of intense interest. Automated molecular recognition in security, defense, and medicine applications, while potentially requiring detection of multiple molecular targets, offers a comparatively less complex framework to initially advance molecular biometrics. Integrated biosensor systems for rapid direct detection of a broad spectrum of biomolecular targets are needed for realization of effective protection, response, and diagnostic scenarios related to a range of threats natural and otherwise, from biowarfare agents to biocontamination of food and water supplies to markers for cancer. The WVNano Initiative targets the exploration of the molecular recognition and transport functions needed to meet these application challenges.
This comprehensive perspective connects the critical NSE research objectives of the WVNano Initiative in molecular recognition with the long-term direction of the NSF Center for Identification Technology Research (CITeR) biometrics.