Inferring the function of genes from synthetic lethal mutations

Techniques for detecting synthetic lethal mutations in double gene deletion experiments are emerging as powerful tool for analysing genes in parallel or overlapping pathways with a shared function. 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)

A framework for modelling Molecular Interaction Maps

Metabolic networks, formed by a series of metabolic pathways, are made of intracellular and extracellular reactions that determine the biochemical properties of a cell, and by a set of interactions that guide and regulate the activity of these reactions. Most of these pathways are formed by an intricate and complex network of chain reactions, and can be represented in a human readable form using graphs which describe the cell cycle checkpoint pathways. This paper proposes a method to represent Molecular Interaction Maps (graphical representations of complex metabolic networks) in Linear Temporal Logic. The logical representation of such networks allows one to reason about them, in order to check, for instance, whether a graph satisfies a given property $\phi$, as well as to find out which initial conditons would guarantee $\phi$, or else how can the the graph be updated in order to satisfy $\phi$. Both the translation and resolution methods have been implemented in a tool capable of addressing such questions thanks to a reduction to propositional logic which allows exploiting classical SAT solvers.Comment: 31 pages, 12 figure

On deducing causality in metabolic networks

© 2008 Bodei et al.; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution Licens

Using a logical model to predict the growth of yeast

<p>Abstract</p> <p>Background</p> <p>A logical model of the known metabolic processes in <it>S. cerevisiae </it>was constructed from iFF708, an existing Flux Balance Analysis (FBA) model, and augmented with information from the KEGG online pathway database. The use of predicate logic as the knowledge representation for modelling enables an explicit representation of the structure of the metabolic network, and enables logical inference techniques to be used for model identification/improvement.</p> <p>Results</p> <p>Compared to the FBA model, the logical model has information on an additional 263 putative genes and 247 additional reactions. The correctness of this model was evaluated by comparison with iND750 (an updated FBA model closely related to iFF708) by evaluating the performance of both models on predicting empirical minimal medium growth data/essential gene listings.</p> <p>Conclusion</p> <p>ROC analysis and other statistical studies revealed that use of the simpler logical form and larger coverage results in no significant degradation of performance compared to iND750.</p

Constitutive relevance and interlevel experiments

One reason for the popularity of Craver's mutual manipulability account of constitutive relevance (MM) is that it seems to make good sense of the experimental practices and constitutive reasoning in the life sciences. Two recent papers (Baumgartner and Gebharter [2016]; Baumgartner and Casini [2017]) propose a theoretical alternative to (MM) in light of several important conceptual objections. Their alternative approach, the No De-Coupling (NDC) account conceives of constitution as a dependence relation which, once postulated, provides the best explanation of the impossibility of breaking the common cause coupling of a macro-level mechanism and its micro-level components. This entails an abductive view of constitutive inference. Proponents of the NDC or abductive account recognize that their discussion leaves open a big question concerning the practical dimension of the notion of constitutive relevance: Is it possible to faithfully reconstruct constitutional reasoning in science in terms of a failure to de-couple, via interlevel experiments, phenomena from their mechanistic constituents? Focusing on the field of memory and LTP research, this paper argues that the abductive account provides a more adequate description of interlevel experiments in neuroscience. We also suggest that the account highlights some significant practical recommendations of how to interpret the findings of interlevel experiments

Constitutive relevance and interlevel experiments

One reason for the popularity of Craver's mutual manipulability account of constitutive relevance (MM) is that it seems to make good sense of the experimental practices and constitutive reasoning in the life sciences. Two recent papers (Baumgartner and Gebharter [2016]; Baumgartner and Casini [2017]) propose a theoretical alternative to (MM) in light of several important conceptual objections. Their alternative approach, the No De-Coupling (NDC) account conceives of constitution as a dependence relation which, once postulated, provides the best explanation of the impossibility of breaking the common cause coupling of a macro-level mechanism and its micro-level components. This entails an abductive view of constitutive inference. Proponents of the NDC or abductive account recognize that their discussion leaves open a big question concerning the practical dimension of the notion of constitutive relevance: Is it possible to faithfully reconstruct constitutional reasoning in science in terms of a failure to de-couple, via interlevel experiments, phenomena from their mechanistic constituents? Focusing on the field of memory and LTP research, this paper argues that the abductive account provides a more adequate description of interlevel experiments in neuroscience. We also suggest that the account highlights some significant practical recommendations of how to interpret the findings of interlevel experiments

Constitutive relevance in interlevel experiments

One reason for the popularity of Craver’s mutual manipulability (MM) account of constitutive relevance is that it seems to make good sense of the experimental practices and constitutive reasoning in the life sciences. Two recent papers (Baumgartner and Gebharter [2016]; Baumgartner and Casini [2017]) propose a theoretical alternative to (MM) in light of several important conceptual objections. Their alternative approach, the no de-coupling (NDC) account, conceives of constitution as a dependence relation that once postulated provides the best explanation of the impossibility of breaking the common cause coupling of a macro-level mechanism and its micro-level components. This entails an abductive view of constitutive inference. Proponents of the NDC or abductive account recognize that their discussion leaves open a big question concerning the practical dimension of the notion of constitutive relevance: Is it possible to faithfully reconstruct constitutional reasoning in science in terms of a failure to de-couple, via interlevel experiments, phenomena from their mechanistic constituents? Focusing on the field of memory and long-term potential (LTP) research, this article argues that the abductive account provides a more adequate description of interlevel experiments in neuroscience. We also suggest that the account highlights some significant practical recommendations of how to interpret the findings of interlevel experiments

An Abductive Argument from Depression and Anxiety to Christian Personal Holiness

The science on pathological depression and anxiety (D&A) describes religion and spirituality\u27s (R/S) insulating and immunizing effects in roughly 72 to 85 percent of all relevant articles. But the descriptivism of science cannot assign any normative value to a theological worldview. Deductive logic favors theism via Leibnizian contingency, Kalām cosmology, objective morality, fine-tuning of the universe, and abstract conceptualism. The information in DNA, the irreducible complexity of intracellular machinery, the improbability of folded proteins, and the support for common modular design over common ancestry establish a design inference for all of life. Unguided naturalistic simulations fail to surmount the complexity barrier of life, diminishing scientific materialism\u27s explanatory power. After philosophical analysis, a cumulative argument using inference to the best explanation (abduction) favors theism over all other worldviews for the complexity of life, the subsequent neurocognitive mechanisms of D&A, and the effects of R/S on D&A. A minimal facts approach establishes Christian theism with positive responses to divine revelation (RDRs) incurring degrees of relative holiness (DRHs). The Christian and non-Christian alike may respond to general revelations in nature and conscience with subsequent DRHs that allow for insulation and immunization against the vicissitudes of life and, therefore, D&A. But the eternal and final solution for D&A is only through a response to the special revelation of the written and living logos with the subsequent imputed holiness of Jesus Christ

Proceedings of the IJCAI-09 Workshop on Nonmonotonic Reasoning, Action and Change

Copyright in each article is held by the authors. Please contact the authors directly for permission to reprint or use this material in any form for any purpose.The biennial workshop on Nonmonotonic Reasoning, Action and Change (NRAC) has an active and loyal community. Since its inception in 1995, the workshop has been held seven times in conjunction with IJCAI, and has experienced growing success. We hope to build on this success again this eighth year with an interesting and fruitful day of discussion. The areas of reasoning about action, non-monotonic reasoning and belief revision are among the most active research areas in Knowledge Representation, with rich inter-connections and practical applications including robotics, agentsystems, commonsense reasoning and the semantic web. This workshop provides a unique opportunity for researchers from all three fields to be brought together at a single forum with the prime objectives of communicating important recent advances in each field and the exchange of ideas. As these fundamental areas mature it is vital that researchers maintain a dialog through which they can cooperatively explore common links. The goal of this workshop is to work against the natural tendency of such rapidly advancing fields to drift apart into isolated islands of specialization. This year, we have accepted ten papers authored by a diverse international community. Each paper has been subject to careful peer review on the basis of innovation, significance and relevance to NRAC. The high quality selection of work could not have been achieved without the invaluable help of the international Program Committee. A highlight of the workshop will be our invited speaker Professor Hector Geffner from ICREA and UPF in Barcelona, Spain, discussing representation and inference in modern planning. Hector Geffner is a world leader in planning, reasoning, and knowledge representation; in addition to his many important publications, he is a Fellow of the AAAI, an associate editor of the Journal of Artificial Intelligence Research and won an ACM Distinguished Dissertation Award in 1990