Heterogeneous biomedical database integration using a hybrid strategy: a p53 cancer research database.

Complex problems in life science research give rise to multidisciplinary collaboration, and hence, to the need for heterogeneous database integration. The tumor suppressor p53 is mutated in close to 50% of human cancers, and a small drug-like molecule with the ability to restore native function to cancerous p53 mutants is a long-held medical goal of cancer treatment. The Cancer Research DataBase (CRDB) was designed in support of a project to find such small molecules. As a cancer informatics project, the CRDB involved small molecule data, computational docking results, functional assays, and protein structure data. As an example of the hybrid strategy for data integration, it combined the mediation and data warehousing approaches. This paper uses the CRDB to illustrate the hybrid strategy as a viable approach to heterogeneous data integration in biomedicine, and provides a design method for those considering similar systems. More efficient data sharing implies increased productivity, and, hopefully, improved chances of success in cancer research. (Code and database schemas are freely downloadable, http://www.igb.uci.edu/research/research.html.)

A Review on the Application of Natural Computing in Environmental Informatics

Natural computing offers new opportunities to understand, model and analyze the complexity of the physical and human-created environment. This paper examines the application of natural computing in environmental informatics, by investigating related work in this research field. Various nature-inspired techniques are presented, which have been employed to solve different relevant problems. Advantages and disadvantages of these techniques are discussed, together with analysis of how natural computing is generally used in environmental research.Comment: Proc. of EnviroInfo 201

RegenBase: a knowledge base of spinal cord injury biology for translational research.

Spinal cord injury (SCI) research is a data-rich field that aims to identify the biological mechanisms resulting in loss of function and mobility after SCI, as well as develop therapies that promote recovery after injury. SCI experimental methods, data and domain knowledge are locked in the largely unstructured text of scientific publications, making large scale integration with existing bioinformatics resources and subsequent analysis infeasible. The lack of standard reporting for experiment variables and results also makes experiment replicability a significant challenge. To address these challenges, we have developed RegenBase, a knowledge base of SCI biology. RegenBase integrates curated literature-sourced facts and experimental details, raw assay data profiling the effect of compounds on enzyme activity and cell growth, and structured SCI domain knowledge in the form of the first ontology for SCI, using Semantic Web representation languages and frameworks. RegenBase uses consistent identifier schemes and data representations that enable automated linking among RegenBase statements and also to other biological databases and electronic resources. By querying RegenBase, we have identified novel biological hypotheses linking the effects of perturbagens to observed behavioral outcomes after SCI. RegenBase is publicly available for browsing, querying and download.Database URL:http://regenbase.org

Ensuring patients privacy in a cryptographic-based-electronic health records using bio-cryptography

Several recent works have proposed and implemented cryptography as a means to preserve privacy and security of patients health data. Nevertheless, the weakest point of electronic health record (EHR) systems that relied on these cryptographic schemes is key management. Thus, this paper presents the development of privacy and security system for cryptography-based-EHR by taking advantage of the uniqueness of fingerprint and iris characteristic features to secure cryptographic keys in a bio-cryptography framework. The results of the system evaluation showed significant improvements in terms of time efficiency of this approach to cryptographic-based-EHR. Both the fuzzy vault and fuzzy commitment demonstrated false acceptance rate (FAR) of 0%, which reduces the likelihood of imposters gaining successful access to the keys protecting patients protected health information. This result also justifies the feasibility of implementing fuzzy key binding scheme in real applications, especially fuzzy vault which demonstrated a better performance during key reconstruction

Monetization of Environmental Externalities (Emissions) from Bioenergy

Bioenergy from agriculture is today in the heart of sustainable development, integrating its key components: environment and climate change, energy economics and energy supply, agriculture, rural and social development. Each bioenergy production route presents externalities that must be assessed in order to compare one bioenergy route to another (bio)energy route. The lack of primary and reliable data on externalities is, nevertheless, an important nontechnological barrier to the implementation of the best (bio)energy routes. In this article, we want to monetize one environmental externality from bioenergy: emissions (GHG: CO2, CH4, N2O, O3; CO, NOx, SO2, metal, and PM). We have to monetize emissions on the basis of their effects on health, global warming, and soil and water quality. Emissions will be quantified through Life Cycle Analysis (LCA) and ECOINVENT database. Impacts on health will be monetized on the basis of mortality (number of life expectancy years lost multiplied by Value Of Life Year (VOLY)) and morbidity (number of ill persons multiplied by Cost Of Illness (COI)). Impacts on global warming will be monetized by Benefits Transfers from the Stern Review and its critics. Finally, impacts on soil and water quality will be monetized by Averting Behaviour or Defensive Expenses methods. Monetization results will be gathered, weighted, and incorporated in states and firms’ decisionmaking tools. They would enhance capacity of policy makers and managers to chose the best (bio)energy routes.Sustainable development, externality, monetization, bioenergy, emissions

TumorML: Concept and requirements of an in silico cancer modelling markup language

This paper describes the initial groundwork carried out as part of the European Commission funded Transatlantic Tumor Model Repositories project, to develop a new markup language for computational cancer modelling, TumorML. In this paper we describe the motivations for such a language, arguing that current state-of-the-art biomodelling languages are not suited to the cancer modelling domain. We go on to describe the work that needs to be done to develop TumorML, the conceptual design, and a description of what existing markup languages will be used to compose the language specification