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Aging kills 150 000 people a day, much more than any other diseases combined. Discovery of a cure for this disease is one of the major challenges of humankind. Unfortunately, with over three hundred theories competing each other other ageing research is rather chaotic and there is no place for integration of diverse knowledge on any level. Aging researchers do not have means for comprehensive analysis of human biology on various levels simultaneously: datasets are not linked, metadata of different datasets do not match, solving of problems require a significant amount of both information technology and biological knowledge.
We started Denigma project that aims to fill this gap by providing a unified knowledge base, normalization of datasets, providing services for aging research both from and outside academia. These tools would allow smooth formation of interdisciplinary research teams and data analysis, fragmentation of aging problems, and delivering small problems for the public to solve. Hence, this will speed up aging research and further develop communities fighting with aging.
Our objectives for a year is to (i) develop a knowledge base for data analysis on aging with a focus on lifespan interventions, (ii) identify and normalize the related datasets, and (iii) use the crowd and aging researchers to form open teams which deliver valid scientific results.
Simplify and speed up data analysis. Having the knowledge base and normalized datasets would significantly decrease data preparation stage, the same interfaces would be used to access data from different datasets.
Enrich data analysis. The knowledge base and normalized datasets would allow to work with multiple datasets from various disciplines simultaneously.
Boost idea generation. Involvement of people both from and outside of academia having different backgrounds and working together will produce larger number of ideas.
Speed up evolution of aging theories. With our framework only good integrated and well-supported theories will survive and mature.
Accelerate aging research. The knowledge base and fragmentation of problems would speed up the overall process of aging research and the identification of novel effective therapeutics.
This project is a fusion of information technology, biology and crowdsourcing and therefore requires the following skills: software development, semantic web and advanced data analytics, biological sciences and networking with longevity communities. Our team has the full skill-set:
To bootstrap this endeavor we would need $300k to ensure that four core developers within our initiative can work full time on it for one year and cover the essential costs for the infrastructure, involvement of external experts and promotion in order to initialize a sustainable framework for Open Distributed Science of Aging Research.
Solving aging requires the construct a Digital Decipher Machine to help creating a crowdsourced web intelligence capable of reverse-engineering the aging process. We initialized the construction of Denigma in order to structure the available data in such a way that aging research can be distributed and the knowledge becomes amenable to global computing and reasoning by machine algorithms.
The achievements of this project so far are the following:
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