:Abstract: Denigma is a Digital Decipher Machine that can encode and decode data in the web. It is specifically devoted to decipher the aging process by utilizing and systematizing the rapidly increasing amount of available biological data and any other information with relevance to aging research. Denigma structures the informatiothe n in form of facts and enables modular access to diverse data and logical reasoning on the constructed knowledge base. This enables decoderly alogorithms to do global inference and pning on web-scale and therefore the identification of high effective interventions by considering all previous knowledge and making high-confidence testable predictions.
.. Denigma is a Manhatten-Project like endeavour of the International Longevity Alliance (ILA) and is its major information technological flagship which is automating the discovery of novel therapeutics that will be tested in a by the ILA proposed testing center [Figure: Roadmap Concept].
Denigma is a project of the International Longevity Alliance and functions as its main information technological platform. One of its aims is to automate the discovery of novel therapeutics to be tested [Figure: The Vision].
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**Figure: The Vision**
The construct of a digital decipher machine will allow the creation of a web intelligence capable of reverse-engineering the aging process within our lifetime.
Specifically Denigma uses advanced information technologies such as semantic web and machine learning bundled with information theory and combined with crowdsourcing for longevity research. Its development is lead by a group of enthusiasts which consists of scientists researching aging and engineers from software development industry as well as social networkers.
The semantic web is an extension of the current world wide web in which meaning is added to the individual information pieces contained in web documents. In its core information is represented in form of triples which are making up the Resource Description Description, a universal language to represent knowledge [Figure: Semantic Web Stack]. Denigma leaverages semantic web technologies and builds on top of it.
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Figure: Semantic Web Stack.
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Figure: Data Units.
A key technology of the required integration of heterogneous data on aging are ontologies, which are like a schema for data and used extensively not only in the semantic web, but also software development and artifical intellegence. Denigma takes advantage of the existing technologies and generates missing and complementing ontologies such as those required for describing the aging process and integration and analysis of heterogenous biological networks [Figure: Ontology Visualization].
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Figure Ontology Development.
Denigma functions also as a communication device that establishes and maintenance of collaborations under the linking researcher project and the world-wide continous longevity meeting.
Overall Denigma establishes an information technology (IT) ecosystem that speeds up anti-aging research and activism, summarizes collected knowledge and infers new knowledge from collected one.
So far Denigma already gathered a tremendous amount of facts about aging research. At the center is the lifespan application which systematizes all data from lifespan studies, over intervention to the individual factors that limit our lifespan. With Denigma it is easily possible to see what has already been achieved in anti-aging experiments and which factors influence aging. Further functional genomics information are utilized such as gene expression activity changes and interactions between biological entities to infer new possible factors with the power to tremendously extend the lifespan.
We are in strongly collaboration with famous aging reasearchers such as Joao Pedro de Magalhaes, the pionier of the genomics of aging and application of systems biology to understand aging, and Aubrey de Grey, the pionier of tackling aging as an enginering problem and the utilization of regenerative medicine to reverse aging, among many others. We recently started the construction of the worlds most comprehensive database on the genetic variants associated with longevity in humans, which will help computer-aided targeted drug discover to extend human healthspan. Further we are developing novel ways of making the aging process visually more attractive therefore also to attract citizen scientists and utilize the power of the crowd to complement automated algorithms to knowledge base creation as well as educate the public about aging as a problem [Figure: Lifespan Charts].
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**Figure: Lifespan Charts.**
There are numerous other applications developed on Denigma that are valuable for aging research, such as an management system that harbours information about experts researching on aging, transhumanists in general and activists as well as functionalities to enable real-time collaborations. Specifically we develop collaborative features to ease collaboration for researchers and activists.
In fact information technology is a field where a group of several developers working full-time can change a lot as features that we develop increase productivity of many of people involved in the field. And as for any IT platform all features of Denigma can also be used in many other fields (both research and not) that provides some extra opportunities.
Computational methods developed on Denigma enable to identify effective therapeutics. Novel interventions can be found be utilizing top-down approache via the use of high-throughput omics data or bottom up via targeted approaches:
Gene expression activity patterns from transcriptomics data of already known lifespan extending interventions are used to derive common molecular signatures associated with longevity. Those signature are then matched with gene expression profiles of drugs that trigger similar gene expression patterns. Drugs that induce similar genes expression changes are with high accuarcy lifespan-extending drugs. Similiar meta -analysing aging-related gene expression changes is use to derive a common molecular signaure associated with aging. By comparing this signature with the gene expression profiles of drugs lets one identify those components that are reverse the age-related gene expression changes. Those drugs that revese agng gene expression changes are powerful anti-aging drugs capable of reversing aging.
Having a comprehensive inventory of all the factors that are associated with lifespan determination enables to apply network-approaches by utilizing interactomics data. For instance, given a list of the genes associated with a certain process like aging, one can apply the guilt-by-association concept which basically states that genes with more interactions than expected by chance with genes associated with a given process are likely to also play a role in that process, i.e. are potential drug targets.
By leverging distributed computing algorithms can identify drugs that fit exactly into the three-dimensional structure of the gene products of for example aging genes.
Logical reasoning of a consistence knowledge base with an apropriate designed ontologies allows to infer the causality of the chain of age-related changes and can suggest via revealing implicit hidden knowledge which therapies are most effective to reverse the those drivers of age-related changes.
Therefore, by utilizing such computational appraches Denigma will be able make recommendations on which experiments need to be done to gain greater insights about the mechanims of aging and how to reverse it as fast as possible by taking into account the current exsiting knowldge and data, as well as providing methods to estimate efficiency of potential life-extending interventions.
Denigma is lies on the intersection of science, collaboration and machine learning [Figure: Denigma Concept]. It enhances scientific discoveries by combining both human intelligence via supporting collaborations and utilizing crowdsourcing with artifical intelligence by machine learning.
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