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Poster was presented at Biotech and Pharma Conference Basel Life 2017, Basel, Switzerland

Understanding of biological process as a whole is a key factor in being able to manage proper targets, avoid side-effects and assign right therapy for the particular combination of conditions. Constantly growing research communication (at a rate of +~5k publications/daily) is a compelling knowledge pull. At the same time, it is huge, sparse and disjointed. Amount of available facts leads to combinatorial explosion in the task of reconstruction the model of a whole particular biological process.Based on the example of questions "Are GPR(x) proteins involved in neuroinflammation? If yes, what is the process exactly?" we demonstrate technical feasibility to infer model of the biological process with the help of machine-reasoning methods.The Poster was presented at BioIT Conference, Boston, USA, 2018

The pathobiochemistry of autism spectrum disorders (ASD) is poorly elucidated and surely multifactorial. Certain nutrients play a role. Gluten and casein have been described most extensively in the literature. Based on clinical observation and using machine reasoning by the sci.AI system, we propose a model which focuses on the centrality of fumaric acid (FA) in ASD pathobiochemistry. As depicted in the Graphical Abstract, the excessive accumulation of FA impairs the microtubule integrity aggravating the neuronal dysfunction in ASD children. Therefore, restricting its accumulation should be considered in the management of ASD.

There are several separate observations found in the research communication. Pro-inflammatory stimuli impact glial cells that response with TNFa, IL-6 and IL-1β, which inhibit glutamate uptake by glial cells [Huichun Tong et al. 2017]. High glutamate concentrations stimulate extrasynaptic NMDA receptors that lead to the calcium influx. [Zhang et al. 2016]. Consequently, elevated cytosolic calcium and activated calpain preceded neurodegeneration [Kurbatskaya et al. 2016]. But no single complete experimental paper describes the whole molecular-level processes of the neuroinflammation (as of beginning of 2018 and to our best knowledge). We utilized machine learning methods to match complementing facts from different papers. The algorithm generates single reasoning chain to hypothesize description of the biological process with the highest possible level of detalization. The reasoning module is a part of the sci.AI platform and analyzes lexical and biological groups of features of the tuples that are semantically extracted from the original research papers. The inferred pathway is visually encoded with spatial (histological) and timeline dimensions. It is done with the aim of communicating the process as close as possible to biological ground truth. Here we present performance of the machine method based on the example of inferred inflammatory cascade and glial-synapse interactions.The Poster was presented at Federation of European Neuroscience Societies (FENS) Forum of Neuroscience, Berlin, Germany, 2018

SARS-CoV-2 suppresses antioxidant recovery system which then unable to balance normal innate immune response. Higlighted molecules can be used as biomarkers of the condition.

There are several separate observations found in the research communication. Pro-inflammatory stimuli impact glial cells that response with TNFa, IL-6 and IL-1β, which inhibit glutamate uptake by glial cells [Huichun Tong et al. 2017]. High glutamate concentrations stimulate extrasynaptic NMDA receptors that lead to the calcium influx. [Zhang et al. 2016]. Consequently, elevated cytosolic calcium and activated calpain preceded neurodegeneration [Kurbatskaya et al. 2016]. But no single complete experimental paper describes the whole molecular-level processes of the neuroinflammation (as of beginning of 2018 and to our best knowledge). We utilized machine learning methods to match complementing facts from different papers. The algorithm generates single reasoning chain to hypothesize description of the biological process with the highest possible level of detalization. The reasoning module is a part of the sci.AI platform and analyzes lexical and biological groups of features of the tuples that are semantically extracted from the original research papers. The inferred pathway is visually encoded with spatial (histological) and timeline dimensions. It is done with the aim of communicating the process as close as possible to biological ground truth. Here we present performance of the machine method based on the example of inferred inflammatory cascade and glial-synapse interactions.

SARS-CoV-2 suppresses antioxidant recovery system which then unable to balance normal innate immune response. Higlighted molecules can be used as biomarkers of the condition.

sci.AI decomposes research literature to basic statements, links them in the semantic graph and makes new research based on the resulting connections. We apply the method to model a process of drugs repositioning for neurodegenerative disorders (NDD). First, we semanticize papers to produce machine-readable versions. The processed literature is then connected in the graph. The platform performs a search within the graph to find candidate drugs and therapies that might be applied for the treatment of the NDD. Finally, the results of this computational method are validated against existing research reports.The poster was presented at Society for Neuroscience (SfN) Conference, Washington, DC, USA, 2017

COVID-19 aggravates already compromised NO production in cohort with G6PD deficiency. Management of NO level can prevent development of severe ARDS.

Understanding of biological process as a whole is a key factor in being able to manage proper targets, avoid side-effects and assign right therapy for the particular combination of conditions. Constantly growing research communication (at a rate of +~5k publications/daily) is a compelling knowledge pull. At the same time, it is huge, sparse and disjointed. Amount of available facts leads to combinatorial explosion in the task of reconstruction the model of a whole particular biological process.Based on the example of questions "Are GPR(x) proteins involved in neuroinflammation? If yes, what is the process exactly?" we demonstrate technical feasibility to infer model of the biological process with the help of machine-reasoning methods.The Poster was presented at BioIT Conference, Boston, USA, 2018

COVID-19 aggravates already compromised NO production in cohort with NOS3 polymorphism. Management of eNOS/iNOS ratio and NO level can prevent development of severe ARDS.