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Integrating Logical Rules Into Neural Multi-Hop Reasoning for Drug Repurposing [article]

Yushan Liu, Marcel Hildebrandt, Mitchell Joblin, Martin Ringsquandl, Volker Tresp
2020 arXiv   pre-print
We propose a novel method that combines these rules with a neural multi-hop reasoning approach that uses reinforcement learning.  ...  We conduct an empirical study based on the real-world task of drug repurposing by formulating this task as a link prediction problem.  ...  Acknowledgements This work has been supported by the German Federal Ministry for Economic Affairs and Energy (BMWi) as part of the project RAKI (no. 01MD19012C).  ... 
arXiv:2007.05292v1 fatcat:sd5ftnax7jawdll3kndhx7slxy

Explainable Biomedical Recommendations via Reinforcement Learning Reasoning on Knowledge Graphs [article]

Gavin Edwards, Sebastian Nilsson, Benedek Rozemberczki, Eliseo Papa
2021 arXiv   pre-print
In other domains, a neurosymbolic approach of multi-hop reasoning on knowledge graphs has been shown to produce transparent explanations.  ...  In this paper, the approach is explored for drug discovery to draw solid conclusions on its applicability.  ...  Acknowledgments The authors would like to thank Fatima Lugtu, Greet De Baets and Piotr Grabowski for their assistance in evaluating the recommendations and explanations.  ... 
arXiv:2111.10625v1 fatcat:7bj5qstez5er5gqdszneidrcdq

Deep Learning applications for COVID-19

Connor Shorten, Taghi M. Khoshgoftaar, Borko Furht
2021 Journal of Big Data  
Within Life Sciences, our survey looks at how Deep Learning can be applied to Precision Diagnostics, Protein Structure Prediction, and Drug Repurposing.  ...  We hope that this survey will help accelerate the use of Deep Learning for COVID-19 research.  ...  For this reason, COVID-19 research has been much more focused on drug repurposing to find treatments.  ... 
doi:10.1186/s40537-020-00392-9 pmid:33457181 pmcid:PMC7797891 fatcat:aokxo63z2rhdpfxo3egyf3xpcm

A Birds Eye View on Knowledge Graph Embeddings, Software Libraries, Applications and Challenges [article]

Satvik Garg, Dwaipayan Roy
2022 arXiv   pre-print
Numerous strategies have been suggested to work out the KGC dependent on different representation procedures intended to embed triples into a low-dimensional vector space.  ...  Subsequently, we explored popular software packages for model training and examine open research challenges that can guide future research.  ...  DeepPath [164] is one of the earliest attempts to use reinforcement learning techniques to estimate multi-hop logic over a KG.  ... 
arXiv:2205.09088v1 fatcat:c4gfzg4ldras3axpf5wvbldstm

Evolving scenario of big data and Artificial Intelligence (AI) in drug discovery

Manish Kumar Tripathi, Abhigyan Nath, Tej P. Singh, A. S. Ethayathulla, Punit Kaur
2021 Molecular diversity  
The development of deep learning neural networks and their variants with the corresponding increase in chemical data has resulted in a paradigm shift in information mining pertaining to the chemical space  ...  This has necessitated the development of newer algorithms and architectures to mine these databases and fulfil the specific needs of various drug discovery processes such as virtual drug screening, de  ...  In contrast, scaffold hopping and QSAR are the widely used methods for ligand-based drug discovery. [19, 30] .  ... 
doi:10.1007/s11030-021-10256-w pmid:34159484 pmcid:PMC8219515 fatcat:p3lsp57x6rbnxgxdu7y5dggdeu

Generative chemistry: drug discovery with deep learning generative models [article]

Yuemin Bian, Xiang-Qun Xie
2020 arXiv   pre-print
The detailed discussions on utilizing cutting-edge generative architectures, including recurrent neural network, variational autoencoder, adversarial autoencoder, and generative adversarial network for  ...  The de novo design of molecular structures using deep learning generative models introduces an encouraging solution to drug discovery in the face of the continuously increased cost of new drug development  ...  DrugBank 51 The DrugBank database combines detailed drug data with comprehensive drug target information https://www.drug Drug repurposing study for existing drugs.  ... 
arXiv:2008.09000v1 fatcat:ivznoc4bsbfoderwr2ted76fiq

How to Valorize Biodiversity? Let's Go Hashing, Extracting, Filtering, Mining, Fishing

Quoc Do, José Medina-Franco, Thomas Scior, Philippe Bernard
2015 Planta Medica  
Karina Martinez-Mayorga for her insightful discussions, stimulating ideas, and fruitful conversations. Conflict of Interest ! The authors declare that they do not have any conflict of interest.  ...  Some of the latter find their role as lead compounds for lead expansion, lead hopping, and scaffold hopping in the desired therapeutic area.  ...  For Kellenberger et al., the reason of natural drugs may be the similarity of interactions of natural products with biosynthetic enzymes and therapeutic targets [53] .  ... 
doi:10.1055/s-0034-1396314 pmid:25714727 fatcat:ytrehxb7q5f77cxceajmr3mgri

Comparative Analysis of Different Machine Learning Classifiers for the Prediction of Chronic Diseases [chapter]

Rajesh Singh, Anita Gehlot, Dharam Buddhi
2022 Comparative Analysis of Different Machine Learning Classifiers for the Prediction of Chronic Diseases  
Precise diagnosis of these diseases on time is very significant for maintaining a healthy life.  ...  A comparative study of different machine learning classifiers for chronic disease prediction viz Heart Disease & Diabetes Disease is done in this paper.  ...  the characteristics of this heat engine as it has a large scope in the energy sector, because besides its limitations Stirling engine when integrated with CSPP can reduce the CO 2 emissions of nearly  ... 
doi:10.13052/rp-9788770227667 fatcat:da47mjbbyzfwnbpde7rgbrlppe

Structure and dynamics of molecular networks: A novel paradigm of drug discovery

Peter Csermely, Tamás Korcsmáros, Huba J.M. Kiss, Gábor London, Ruth Nussinov
2013 Pharmacology and Therapeutics  
It is shown how network techniques can help in the identification of single-target, edgetic, multi-target and allo-network drug target candidates.  ...  drug development costs.  ...  colleagues for reading the original version of the paper and for valuable suggestions.  ... 
doi:10.1016/j.pharmthera.2013.01.016 pmid:23384594 pmcid:PMC3647006 fatcat:osjkz6kpr5gzxomqlyenla2fvq

The 18th European Symposium on Quantitative Structure–Activity Relationships

Anna Tsantili-Kakoulidou, Dimitris K Agrafiotis
2011 Expert Opinion on Drug Discovery  
the CDK1 inhibitory activity of the pyrrolo [2,3-a]carbazole scaffold. 4 Molecular modeling and docking simulation studies explored the CDK1 binding mode of this core and especially its positioning into  ...  Furthermore, the conducted docking studies elucidated the possible alternative binding mode of the ligands into the ATP binding cleft and assigned their physicochemical and structural features which promote  ...  Rules-of-thumb for evaluating potential drug molecules, such as Lipinski's Rule of Five, are commonly used because they are easy to understand and translate into practice.  ... 
doi:10.1517/17460441.2011.560604 pmid:22646021 fatcat:tb4bhvtnpzahxm4xba7iw4afuy

Deep Reinforcement Learning, a textbook [article]

Aske Plaat
2022 arXiv   pre-print
The book is written for graduate students of artificial intelligence, and for researchers and practitioners who wish to better understand deep reinforcement learning methods and their challenges.  ...  Developments go quickly, and we also cover advanced topics: deep multi-agent reinforcement learning, deep hierarchical reinforcement learning, and deep meta learning.  ...  The eld of symbolic reasoning is based on logic, it is one of the earliest success stories in arti cial intelligence.  ... 
arXiv:2201.02135v2 fatcat:3icsopexerfzxa3eblpu5oal64

Can robots make good models of biological behaviour?

B Webb
2001 Behavioral and Brain Sciences  
The explication and justification of this approach are here placed within a framework for describing and comparing models in the behavioural and biological sciences.  ...  ACKNOWLEDGMENT We thank the National Science Foundation and the Gatsby Foundation for the support of the Telluride Workshop on Neuromorphic Engineering where this work was performed.  ...  ACKNOWLEDGMENTS Research and preparation for this commentary have been supported by grant NAGS-8781 from the National Aeronautics and Space Administration, and grant BCS 92-16562 from the National Science  ... 
pmid:12412325 fatcat:xzdirg5xezamdpqc5k42qydf3m

A Systems Thinking Approach to identify Leverage Points for Sustainability: A Case Study in the Cat Ba Biosphere Reserve, Vietnam

Nam C. Nguyen, Ockie J. H. Bosch
2012 Systems research and behavioral science  
Hence the identification of a symptom may become a multi-level logic, namely fuzzy logic.  ...  That this field has been active for fifty years without a consensus on the criteria for a GTS, on strict rules for abstraction and deabstraction, as well as proof of isomorphy may be the reason for its  ...  The schedule will provide ample time for relaxed social and professional interaction.  ... 
doi:10.1002/sres.2145 fatcat:2gofah363vaq3g43dbepghn4nu

Deep Learning on Attributed Graphs: A Journey from Graphs to Their Embeddings and Back [article]

Martin Simonovsky
2019 arXiv   pre-print
A graph is a powerful concept for representation of relations between pairs of entities.  ...  We concentrate on two important primitives: embedding graphs or their nodes into a continuous vector space representation (encoding) and, conversely, generating graphs from such vectors back (decoding)  ...  Acknowledgements Foremost, I would like to express gratitude to my supervisor Nikos Komodakis for accepting me as his student and securing funding for the whole period, for useful discourses and insights  ... 
arXiv:1901.08296v1 fatcat:vp6uzgasnrgzpoaqv2dni5bega

Security in product lifecycle of IoT devices: A survey

Narges Yousefnezhad, Avleen Malhi, Kary Främling
2020 Journal of Network and Computer Applications  
Further, we present prominent solutions for addressing product lifecycle security in IoT.  ...  In that regard, we provide a comprehensive comparison of state-of-the-art surveys in an initial phase which concentrate on distinct parameters required for IoT security.  ...  This is the main reason for device failures in the network, as Beresford (2016) reports.  ... 
doi:10.1016/j.jnca.2020.102779 fatcat:junhktapajc75px3n2x6j7tzou
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