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Modelling Inhibition in Metabolic Pathways Through Abduction and Induction [chapter]

Alireza Tamaddoni-Nezhad, Antonis Kakas, Stephen Muggleton, Florencio Pazos
<span title="">2004</span> <i title="Springer Berlin Heidelberg"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
We show how we can model, within Abductive Logic Programming (ALP), inhibition in metabolic pathways and use abduction to generate facts about inhibition of enzymes by a particular toxin (e.g.  ...  In particular, using Progol 5.0 where the processes of abduction and inductive generalization are integrated enables us to learn such general rules.  ...  This work was supported by the DTI project "MetaLog -Integrated Machine Learning of Metabolic Networks applied to Predictive Toxicology".  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-540-30109-7_23">doi:10.1007/978-3-540-30109-7_23</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/5jfams3bhjhjbmjl6dp2kwgwji">fatcat:5jfams3bhjhjbmjl6dp2kwgwji</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20070628103619/http://pdg.cnb.uam.es/pazos/papers/ILP_04.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/78/f1/78f1cc35cea3d510b8c6aa9c583fc71a98e56b54.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-540-30109-7_23"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Application of abductive ILP to learning metabolic network inhibition from temporal data

Alireza Tamaddoni-Nezhad, Raphael Chaleil, Antonis Kakas, Stephen Muggleton
<span title="2006-06-30">2006</span> <i title="Springer Nature"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/h4nnd7sxwzcwhetu5qkjbcdh6u" style="color: black;">Machine Learning</a> </i> &nbsp;
In this paper we use a logic-based representation and a combination of Abduction and Induction to model inhibition in metabolic networks.  ...  In modelling the phenomenon of inhibition in metabolic networks, background knowledge is used which describes the network topology and functional classes of inhibitors and enzymes.  ...  Crockford and T. Ebbels for preparing the NMR data. This work was supported by the DTI project "MetaLog-Integrated Machine Learning of Metabolic Networks applied to Predictive Toxicology".  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s10994-006-8988-x">doi:10.1007/s10994-006-8988-x</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/dzxlgjusujagbbpnjiyqcx5jpe">fatcat:dzxlgjusujagbbpnjiyqcx5jpe</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20080221163935/http://pubs.doc.ic.ac.uk/abductive-ilp-bioinformatics/abductive-ilp-bioinformatics.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/df/71/df71eacebf88202502ca3b7e6fdd8f924a1df410.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s10994-006-8988-x"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Modeling the effects of toxins in metabolic networks

Alireza Tamaddoni-Nezhad, Raphael Chaleil, Antonis Kakas, Michael Sternberg, Jeremy Nicholson, Stephen Muggleton
<span title="">2007</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/pmtdj6zv2fdcvholrbp6p43mxm" style="color: black;">IEEE Engineering in Medicine and Biology Magazine</a> </i> &nbsp;
A bduction and induction are two forms of reasoning that have been widely used in machine learning. The combination of abduction and induction has recently been explored from a number of angles [1] .  ...  Interested readers are referred to [13] for more information on the use of abduction and induction in these studies.  ...  This work was supported by the DTI project "MetaLog-Integrated Machine Learning of Metabolic Networks applied to Predictive Toxicology."  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/memb.2007.335590">doi:10.1109/memb.2007.335590</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/17441607">pmid:17441607</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/t5qychqfejhppghqitgfgkaigu">fatcat:t5qychqfejhppghqitgfgkaigu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20070824024135/http://www.doc.ic.ac.uk/~shm/Papers/ieeemetabduce.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/82/9f/829fc654e4ae2a8c48feaa13b5b02bfec09684d1.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/memb.2007.335590"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Machine Learning for Systems Biology [chapter]

S. H. Muggleton
<span title="">2005</span> <i title="Springer Berlin Heidelberg"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
Secondly, Bayes' networks have been machine-learned to provide causal maps of the effects of toxins on the network of metabolic reactions within cells.  ...  Thirdly, in a complementary study KEGG pathways are being used as background knowledge for explaining the same data using a model constructed using Abductive ILP, a logic-based machine learning technique  ...  This work was supported by the DTI Beacon project "Metalog -Integrated Machine Learning of Metabolic Networks Applied to Predictive Toxicology", Grant Reference QCBB/C/012/00003, the ESPRIT IST project  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/11536314_27">doi:10.1007/11536314_27</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/w4fdczk6kzh6fa5piq3ydamely">fatcat:w4fdczk6kzh6fa5piq3ydamely</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20061014224915/http://pubs.doc.ic.ac.uk/machine-learning-sys-biology/machine-learning-sys-biology.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/3a/87/3a87c3104202e3095d9a618d4588b26006c21ce2.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/11536314_27"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Learning probabilistic logic models from probabilistic examples

Jianzhong Chen, Stephen Muggleton, José Santos
<span title="2008-08-06">2008</span> <i title="Springer Nature"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/h4nnd7sxwzcwhetu5qkjbcdh6u" style="color: black;">Machine Learning</a> </i> &nbsp;
We revisit an application developed originally using abductive Inductive Logic Programming (ILP) for modeling inhibition in metabolic networks.  ...  Instead of learning logic models from non-probabilistic examples as done in ILP, the PILP approach applied in this paper is based on a general technique for introducing probability labels within a standard  ...  Acknowledgements The authors would like to acknowledge support from the Royal Academy of Engineering/Microsoft Research Chair on 'Automated Microfluidic Experimentation using Probabilistic Inductive Logic  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s10994-008-5076-4">doi:10.1007/s10994-008-5076-4</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/19888348">pmid:19888348</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC2771423/">pmcid:PMC2771423</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/vpnu5djquncwfgsfvxlzsaoe3i">fatcat:vpnu5djquncwfgsfvxlzsaoe3i</a> </span>
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Automatic Revision of Metabolic Networks through Logical Analysis of Experimental Data [chapter]

Oliver Ray, Ken Whelan, Ross King
<span title="">2010</span> <i title="Springer Berlin Heidelberg"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
With respect to this model, a mixture of abductive and inductive inference is used to compute a set of minimal revisions needed to make a given network consistent with some observed data.  ...  , enzyme inhibitions, and metabolic reactions.  ...  Conclusions This paper presented a logical method for the automatic revision of metabolic networks through abductive and inductive analysis of experimental data.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-13840-9_18">doi:10.1007/978-3-642-13840-9_18</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/mwcecuiej5gird6dydsvqokq3y">fatcat:mwcecuiej5gird6dydsvqokq3y</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20151206065210/http://www.cs.bris.ac.uk/Publications/Papers/2001245.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/33/29/3329e9c73596f5da9d1a36143f3b67bd27940926.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-13840-9_18"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Towards a Rational Approach for the Logical Modelling of Inhibition in Metabolic Networks

Oliver Ray
<span title="">2009</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/6fvrx6ji2nauffetsxyi4abwam" style="color: black;">2009 International Conference on Advanced Information Networking and Applications Workshops</a> </i> &nbsp;
This paper makes two contributions towards the logical modelling of inhibition in metabolic networks. First it exposes the logical inconsistency of an existing state-of-the-art metabolic theory.  ...  Underlying this work is use of nonmonotonic logic programs to represent and reason about competing inhibitory effects on the net concentrations of metabolites in enzyme-catalysed biochemical networks.  ...  Learning Task The new metabolic theory is intended to infer abductive and inductive hypotheses for predicate inhibit/2 that logically entail (according to the credulous stable model semantics) a set of  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/waina.2009.186">doi:10.1109/waina.2009.186</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/aina/Ray09.html">dblp:conf/aina/Ray09</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/kiq4mgluw5cifiyz4xhfochfdu">fatcat:kiq4mgluw5cifiyz4xhfochfdu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20110401053145/http://www.cs.bris.ac.uk/Publications/Papers/2001071.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/31/b3/31b3eede8fb2c1b23915714881224fd85a90942c.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/waina.2009.186"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Logic-Based Steady-State Analysis and Revision of Metabolic Networks with Inhibition

Oliver Ray, Ken Whelan, Ross King
<span title="">2010</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ko5glutn75hm7kdxq25qkix3k4" style="color: black;">2010 International Conference on Complex, Intelligent and Software Intensive Systems</a> </i> &nbsp;
This paper presents a qualitative logic-based method for the steady-state analysis and revision of metabolic networks with inhibition.  ...  We show how this can be done in a nonmonotonic logic programming setting and discuss the challenges that arise when metabolic cycles or mutual inhibitions occur in the underlying network.  ...  ACKNOWLEDGMENTS This work was supported by a RCUK fellowship and BBSRC Modelling Apprentice Grant (BB/G000662/1).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/cisis.2010.184">doi:10.1109/cisis.2010.184</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/cisis/RayWK10.html">dblp:conf/cisis/RayWK10</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/icwzu6gunzfwfmlznbygchcxje">fatcat:icwzu6gunzfwfmlznbygchcxje</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20110401054045/http://www.cs.bris.ac.uk/Publications/Papers/2001157.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/cc/9c/cc9c894190d7019d4167d2a52c1ff3b8aef0cf02.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/cisis.2010.184"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

A Nonmonotonic Logical Approach for Modelling and Revising Metabolic Networks

Oliver Ray, Ken Whelan, Ross King
<span title="">2009</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ko5glutn75hm7kdxq25qkix3k4" style="color: black;">2009 International Conference on Complex, Intelligent and Software Intensive Systems</a> </i> &nbsp;
This paper describes a new logic-based approach for representing and reasoning about metabolic networks.  ...  Then it shows how a nonmonotonic reasoning system called XHAIL can be used as a practical method for learning and revising such metabolic networks from observational data.  ...  Then it shows how a nonmonotonic reasoning system called XHAIL (eXtended Hybrid Abductive Inductive Learning) [13] can be used as a practical method for learning and revising such metabolic networks  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/cisis.2009.175">doi:10.1109/cisis.2009.175</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/cisis/RayWK09.html">dblp:conf/cisis/RayWK09</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/pi7itblsobh4dbep6wyzahuj3y">fatcat:pi7itblsobh4dbep6wyzahuj3y</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20090625180724/http://www.cs.bris.ac.uk/Publications/Papers/2001003.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/86/c7/86c7fdbb7164b9db073922fcb4d22804a95663ec.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/cisis.2009.175"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Nonmonotonic Learning in Large Biological Networks [chapter]

Stefano Bragaglia, Oliver Ray
<span title="">2015</span> <i title="Springer International Publishing"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
This paper introduces a new open-source implementation of a nonmonotonic learning method called XHAIL and shows how it can be used for abductive and inductive inference on metabolic networks that are many  ...  We investigate the system's scalability in a case study involving real data previously collected by a Robot Scientist and show how it led to the discovery of an error in a whole-organism model of yeast  ...  The task of revising (as opposed to merely extending) such models is a nonmonotonic ILP problem addressed by methods like eXtended Hybrid Abductive Inductive Learning (XHAIL) [15, 16, 14] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-319-23708-4_3">doi:10.1007/978-3-319-23708-4_3</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/nzd33htnufggldok367v5vx5be">fatcat:nzd33htnufggldok367v5vx5be</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180722044705/https://research-information.bristol.ac.uk/files/70795072/Oliver_Ray_Nonmonotonic_Learning_in_Large_Biological_Networks.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/91/99/9199df8400e030b570a0f0cfcc1fd0712507e744.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-319-23708-4_3"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Completing causal networks by meta-level abduction

Katsumi Inoue, Andrei Doncescu, Hidetomo Nabeshima
<span title="2013-04-03">2013</span> <i title="Springer Nature"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/h4nnd7sxwzcwhetu5qkjbcdh6u" style="color: black;">Machine Learning</a> </i> &nbsp;
By representing rule structures of a problem in a form of causal networks, meta-level abduction infers missing links and unknown nodes from incomplete networks to complete paths for observations.  ...  Reasoning in networks with inhibition involves nonmonotonic inference, which can be realized by making default assumptions in abduction.  ...  colleagues of the Systems Resilience project for discussions on robustness, Philip Reiser for his early attempt to complete biological networks by SOLAR, and the reviewers of this paper for their many  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s10994-013-5341-z">doi:10.1007/s10994-013-5341-z</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/w2i25sbowfadrldsjukgdp65ia">fatcat:w2i25sbowfadrldsjukgdp65ia</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190503043657/https://link.springer.com/content/pdf/10.1007%2Fs10994-013-5341-z.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/58/78/5878bb92e3063e02f3cf2a76ce0709d73a73e91f.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s10994-013-5341-z"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Inferring the Function of Genes from Synthetic Lethal Mutations

Oliver Ray, Christopher H. Bryant
<span title="">2008</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ko5glutn75hm7kdxq25qkix3k4" style="color: black;">2008 International Conference on Complex, Intelligent and Software Intensive Systems</a> </i> &nbsp;
This paper introduces a logic-based approach that uses synthetic lethal mutations for mapping genes of unknown function to enzymes in a known metabolic network.  ...  We show how such mappings can be automatically computed by a logical learning system called eXtended Hybrid Abductive Inductive Learning (XHAIL).  ...  To do this, we will generalise existing logic programming models of metabolic inhibition [9] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/cisis.2008.124">doi:10.1109/cisis.2008.124</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/cisis/RayB08.html">dblp:conf/cisis/RayB08</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/uc7zc4od3zeanaaklwahnqhk2i">fatcat:uc7zc4od3zeanaaklwahnqhk2i</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170923002740/http://usir.salford.ac.uk/17388/5/bryant_ieee08.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/fb/39/fb399079af894e020743a862164c502ec1a46841.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/cisis.2008.124"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Machine Learning Methods for Analysis of Metabolic Data and Metabolic Pathway Modeling

Miroslava Cuperlovic-Culf
<span title="2018-01-11">2018</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ie7tehbfsfhs5pdyyt2rrdmnpm" style="color: black;">Metabolites</a> </i> &nbsp;
In this context, machine learning has aided the development of metabolic networks, the calculation of parameters for stoichiometric and kinetic models, as well as the analysis of major features in the  ...  To a lesser extent, machine learning has also been utilized to take advantage of the increasing availability of genomics and metabolomics data for the optimization of metabolic network models and their  ...  Acknowledgments: With the current explosion of the utilization of machine learning in biology, it was not possible to include all examples of applications in system biology, and unfortunately, many fascinating  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/metabo8010004">doi:10.3390/metabo8010004</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/29324649">pmid:29324649</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC5875994/">pmcid:PMC5875994</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/hdzmuzagcjbolhx6hpr4grvw24">fatcat:hdzmuzagcjbolhx6hpr4grvw24</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180727084939/https://res.mdpi.com/def50200c3b4186a9417d7beddcd90c185fe23ca58a7eb4a6072bb4ad8e26c4f9d08c141ae6176515f82a236044892c9190fe907020733da57e953dfd2b71d8786b35572589d9b92e0b015fd83ba6cd6ff98127f8ad50b1b8c773544002494395f8984eff2e5516307178c79a72c907b0936b2c74dad036415727f534c69bf12fbf5f9869b249a690a692c1e821c8bc9f388d152c76b9935d752f2eeb93bd8?filename=&amp;attachment=1" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/4e/dd/4edd70173c73d7a0805124c25c1e7f1081633cc7.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/metabo8010004"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5875994" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Automated Scientific Assistant for Cancer and Chemoprevention [chapter]

Sotiris Lazarou, Antonis C. Kakas, Christiana Neophytou, Andreas Constantinou
<span title="">2013</span> <i title="Springer Berlin Heidelberg"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/kss7mrolvja63k4rmix3iynkzi" style="color: black;">IFIP Advances in Information and Communication Technology</a> </i> &nbsp;
assistant for the biologists to help them in thinking about their experimental results and the possible further investigation of the phenomena of interest.  ...  Starting from the general hypotheses that Scientific Modeling is inextricably linked to abductive reasoning, we aim to develop a general logical model of cell signalling and to provide an automated scientific  ...  Related Work There are several earlier works of Symbolic Systems Biology which also use a form of logical modeling within Logic Programming (Abductive or Inductive) and rely on abductive and/or inductive  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-41142-7_11">doi:10.1007/978-3-642-41142-7_11</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/rap5kyx2fvht7mt7stwscmcq34">fatcat:rap5kyx2fvht7mt7stwscmcq34</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180725024940/https://link.springer.com/content/pdf/10.1007%2F978-3-642-41142-7_11.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/f4/9a/f49a56e1a52d4989fbbe28eb3df65a129e01a75f.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-41142-7_11"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Nonmonotonic abductive inductive learning

Oliver Ray
<span title="">2009</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/gyhc4ppmyjfm5a64dneqesv7ka" style="color: black;">Journal of Applied Logic</a> </i> &nbsp;
This is done by lifting an existing method called Hybrid Abductive Inductive Learning (HAIL) from Horn clauses to normal logic programs.  ...  By contrast, Abductive Logic Programming (ALP), a related task concerned with explaining observations with respect to a prior theory, has been well studied and applied in the context of normal logic programs  ...  Acknowledgements The author is grateful to Dalal Alrajeh, Krysia Broda, Domenico Corapi and Alessandra Russo for useful discussions.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.jal.2008.10.007">doi:10.1016/j.jal.2008.10.007</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/2gniyfpervfh5l6iqislsghdxu">fatcat:2gniyfpervfh5l6iqislsghdxu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20171004011006/http://publisher-connector.core.ac.uk/resourcesync/data/elsevier/pdf/d5e/aHR0cDovL2FwaS5lbHNldmllci5jb20vY29udGVudC9hcnRpY2xlL3BpaS9zMTU3MDg2ODMwODAwMDY4Mg%3D%3D.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/54/3b/543b378a8964ec1b6ee5697c09b1809c1fc26720.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.jal.2008.10.007"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> elsevier.com </button> </a>
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