Learning Qualitative Metabolic Models
نویسندگان
چکیده
The ability to learn a model of a system from observations of the system and background knowledge is central to intelligence, and the automation of the process is a key research goal of Artificial Intelligence. We present a modellearning system, developed for application to scientific discovery problems, where the models are scientific hypotheses and the observations are experiments. The learning system, Qoph learns the structural relationships between the observed variables, known to be a hard problem. Qoph has been shown capable of learning models with hidden (unmeasured) variables, under different levels of noise, and from qualitative or quantitative input data.
منابع مشابه
EQML- An Evolutionary Qualitative Model Learning Framework
In this paper, an Evolutionary Qualitative Model Learning Framework (EQML) is proposed and tested by learning the qualitative metabolic models under the condition of incomplete knowledge. JMorven, a fuzzy qualitative reasoning engine, is slightly modified and integrated into the framework as a sub module to represent and verify the learnt models. Three metabolic compartment models are tested by...
متن کاملAdvanced Experiments for Learning Qualitative Compartment Models
In this paper, the learning of qualitative twocompartment metabolic models is studied under the conditions of different types and numbers of hidden variables. For each condition, all the experiments, each of which takes one of the subsets of the complete qualitative states as training data, are tested one by one. In order to conduct the experiments more efficiently, a backtracking algorithm wit...
متن کاملLearning Qualitative Causal Models via Generalization & Quantity Analysis
Learning causal models is a central problem of qualitative reasoning. We describe a simulation of learning causal models from exemplars that uses progressive alignment and qualitative process theory to derive plausible qualitative causal models from observations. We show how protohistories can be created via progressive alignment and used to infer causality. The result, a causal corpus, can mak...
متن کاملLearning Qualitative Models
task, and building qualitative models is no exception. One way of automating this task is by means of machine learning. Observed behaviors of a modeled system are used as examples for a learning algorithm that constructs a model that is consistent with the data. In this article, we review approaches to learning qualitative models, either from numeric data or qualitative observations. We describ...
متن کاملMetStabOn-Online Platform for Metabolic Stability Predictions.
Metabolic stability is an important parameter to be optimized during the complex process of designing new active compounds. Tuning this parameter with the simultaneous maintenance of a desired compound's activity is not an easy task due to the extreme complexity of metabolic pathways in living organisms. In this study, the platform for in silico qualitative evaluation of metabolic stability, ex...
متن کامل