created on June 17, 2013, 12:39 p.m. by Hevok & updated on June 17, 2013, 10:21 p.m. by antonkulaga
: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 information in the form of facts and enables modular access to diverse data and logical reasoning on the constructed knowledge base. This enables decoding algorithms to perform global inference and planning on web-scale and therefore a the identification of effective interventions by considering all the previous knowledge and making high confident and testable predictions.
.. The Problem of Aging and Approaches to its Amelioration
.. The combination of machine and human intelligence is crucial for reverse-engineering the aging process and for developing effective and promising therapies to ameliorate aging.
Aging is an enormous problem that needs a Manhatten-scale Project to be addressed. Such a project is not possible without establishing an extensive information technological platform that will be used for data unification, provide collaboration tools for researchers and longevity activists and automate the discovery of novel therapeutics to be tested.
That is why the International Longevity Alliance (ILA) initiated the construction of a digital decipher machine, Denigma [http://denigma.de], to reverse-engineer the aging process, make aging research more collaborative as well as efficient and facilitate the discovery of powerful therapeutics to ameliorate the degenerative aging process.
Denigma is a project of the ILA, it also functions as its main information technological platform with the long term aim to automate the discovery of novel therapeutics to be tested. Such discoveries will be a basement for a huge number of potential interventions that in their turn will create the need to establish a lifeextension testing center [Figure: The Vision].
.. figure:: http://dgallery.s3.amazonaws.com/roadmap_concept.svg
Figure: The Vision.
The construction of a digital decipher machine will allow the creation of a web intelligence capable of reverse-engineering the aging process. 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 consisting of aging research scientists and software development engineers, as well as social networkers which all together form the General Computing Initiative (GCI).
Currently biomedical knowledge is scattered in heterogeneous formats. It is present in the form of unstructured academic articles, semi-structured datasets, structured databases and non-accessible in the minds of experts. This renders such heterogeneous knowledge inaccessible for global computing [Attwood et al., 2009].
In order to provide a holistic view for researchers and run various machine learning algorithmes to infer new knowledge, the data should be represented in a well-structured format. This format should be both machine and human readable at the same time. For this we need a knowledge graph and the semantic web is the most suitable technology as it is widely accepted standard and was initialy developed in order to provide a new generation of internet that is knoweldge based.
A key technology to enable such a multi-layered data integration is ontology engineering. An ontology is an explicit formal specification of a shared conceptualization [Gruber T, 1995]. It is a basis for so-called Semantic Web Stack, a set of technologies that let researchers describe heterogeneous data and run reasoning computer algorithms over it.
.. figure:: http://dgallery.s3.amazonaws.com/semantic_web_technology_stack.png
Figure: Semantic Web Stack.
In order to create a semantic graph the knowledge from research papers in the form of free text needs to be converted into a structured form, while individual articles, datasets and databases need to be mapped for modular access and converted into the same structure. Ontologies specific for aging research are necessary and being developed on Denigma. A collective effort is needed to establish the initial structure of the data. Data annotation and ontology creation processes can be automated, but only partially and therefore require human reasoning.
Linked data allows to combine machine learning with croudsourcing approach where a lot of tasks that need "human computations" are effectively outsourced to the crowd. Our crowdsourcing infrastructure is made to attract longevity activists to help scientists, complement and improve machine learning where humans do what machine cannot do well.
Denigma itself the result of crowdsourcing effort of researchers in aging and longevity as well as scientists from other fields.
http://denigma.de/data/entry/deciphering-aging
For deciphering aging we need to have a comprehensive and consistent knowledge.
So far Denigma already has gathered a tremendous amount of facts about aging research. At the center of it is the Lifespan application which systematizes data from lifespan studies, ranging from lifespan experiments, over extending interventions to individual factors that limit the 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 capable of extending the lifespan.
We work in strong collaboration with leading reasearchers of aging such as João Pedro de Magalhães, the pionier of the genomics of aging and of the application of systems biology on aging research, and Aubrey de Grey, the pionier of tackling aging as an enginering problem and the utilization of regenerative medicine to reverse aging, among many other scientists.
We recently started the construction of the world's most comprehensive database on the genetic variants associated with longevity in humans, which will help computer-aided targeted drug discovery to be used to extend the human healthspan.
Further we are developing novel ways of making the aging process visually more attractive, so as to engage citizen scientists and utilize the power of the crowd to complement automated algorithms to knowledge base creation as well as educate the public about the problem of aging [Figure: Lifespan Charts].
.. figure:: http://dgallery.s3.amazonaws.com/lifespan_charts.png
**Figure: Lifespan Charts.**
There are numerous other applications developed on Denigma that are valuable for aging research, such as a semantic menagement system that harbours information about experts researching on aging, transhumanists and life extension activists, as well as functionalities to enable real-time collaborations. Specifically we develop collaborative features to ease collaboration for researchers and activists.
Computational methods developed on Denigma enable to identify effective therapeutics. Novel interventions can be found be utilizing top-down approaches via the use of high-throughput omics data or bottom-up targeted approaches, including:
Gene expression activity patterns from transcriptomics data of already known lifespan extending interventions are used to derive common molecular signatures associated with longevity. Those signatures are then matched with gene expression profiles of drugs that trigger similar gene expression patterns. Drugs that induce similar gene expression changes are with high accuracy lifespan-extending drugs. Similiar meta-analysis of aging-related gene expression changes is used to derive a common molecular signaure associated with aging. The comparison of this signature with the gene expression profiles of drugs allows the researchers to identify those components that reverse the age-related gene expression changes. Those drugs that reverse aging gene expression changes can be 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 the process of aging, the researcher can apply the guilt-by-association concept which basically states that genes with more interactions than expected by chance with genes associated with the given process are likely to also play a role in that process, i.e. are potential drug targets.
By leveraging distributed computing algorithms, we can identify drugs that fit exactly into the three-dimensional structure of the gene products of, for example, aging genes. This approach allows to develop drugs with specific
As mutual information provides the exact estimate of similarity between various model systems, it will be possible to predict the efficacy of a yet untested drug or treatment using the estimates of its similarity (mutual information) with other tested drugs and treatments along with the similarity of model systems to which they are applied.
Logical reasoning of a consistence knowledge base with apropriately 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 drivers of age-related changes.
Therefore, by utilizing such computational appraches, the Denigma will be able to suggest experiments to provide insights into the mechanims of aging and their potential reversal, taking into account the current exsiting knowldge and data, and to provide methods to estimate the efficiency of potential life-extending interventions.
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 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-related and unrelated) that provides some extra opportunities.
We are developing tools and applications which are used primarly for research on longevity. We are also training the crowd in programming to fascilitate development. Some of software we are producing are of general usability while others are domain specific. Those software that we develop can have the potential to be commercialed.
Some of the Denigma applications include:
Denigma lies on the intersection of science, collaboration and machine learning [Figure: Denigma Concept]. It enhances scientific discoveries by combining human and machine intelligence, via supporting collaborations and utilizing crowdsourcing with artifical intelligence and machine learning.
.. figure:: http://dgallery.s3.amazonaws.com/denigma.png
.. We have already ensured that the data can be accessed. .. 1. Conceptual picture with three networks 2. Graph visualization 3. Lifespan charts (or curve) 4. Age-related disease 5. Ontology graph of age-related deceases 6. Age-related changes graph 7. Screenshot with aging factors 8. Prezi presentation with circles 9. Semantic Web Stack
Comment on This Data Unit