Carnosine (beta-alanyl-L-histidine) and homocarnosine (gamma-aminobutyric acid-L-histidine) are two naturally occurring dipeptides with potential neuroprotective and neurotransmitter functions in the brain. Peptidase activities degrading both carnosine and homocarnosine have been described previously, but the genes linked to these activities were unknown. Here we present the identification of t...

This paper investigates the implications of example weighting in subgroup discovery by comparing three state-of-the-art subgroup discovery algorithms, APRIORI-SD, CN2-SD, and SubgroupMiner on a real-life data set. While both APRIORI-SD and CN2-SD use example weighting in the process of subgroup discovery, SubgroupMiner does not. Moreover, APRIORI-SD uses example weighting in the post-processing...

We present a novel approach to machine learning, called ABML (argumentation based ML). This approach combines machine learning from examples with concepts from the field of argumentation. The idea is to provide expert’s arguments, or reasons, for some of the learning examples. We require that the theory induced from the examples explains the examples in terms of the given reasons. Thus argument...

Scorpion β-toxins bind to the voltage-sensing domain of voltage-gated sodium (NaV) channels and trap the voltage-sensing domain in the activated state. Two structurally similar β-toxins from scorpions, Css4 and Cn2, selectively target different subtypes of mammalian NaV channels. While the receptor site on the channels is known, the functional surface of the toxins remains to be understood. Her...

The subgroup discovery, domain of application of CN2-SD, is defined as: ‘‘given a population of individuals and a property of those individuals, we are interested in finding a population of subgroups as large as possible and have the most unusual statistical characteristic with respect to the property of interest’’. The subgroup discovery algorithm CN2-SD, based on a separate and conquer strate...

The dinitrides CN2, SiN2, and GeN2 in assumed pyrite-type structures are studied by means of density functional theory using both ultrasoft pseudopotentials and the augmented spherical wave (ASW) method. The former two materials constitute the large-x limit of the broader class of CNx and SiNx compounds, which are well known for their interesting mechanical and electronic properties. For CN2 a ...

When applying an unordered set of classification rules, the rules may assign more than one class to a particular example. Previous methods of resolving such conflicts between rules include using the most frequent class in the conflicting rules (as done in CN2) and using näıve Bayes to calculate the most probable class. An alternative way of solving this problem is presented in this paper: by ge...

Algorithms for induction of concept descriptions from examples are important tools in the fields of machine learning and knowledge discovery in databases. This paper presents an induction algorithm, named PA3, that learns a set of ordered rules from examples. Functionally inspired in AQ and CN2, this algorithm attempts to generalize the learned rules during the induction process and introduces ...

The CN2 algorithm induces an ordered list of classiication rules from examples using entropy as its search heuristic. In this short paper, we describe two improvements to this algorithm. Firstly, we present the use of the Laplacian error estimate as an alternative evaluation function and secondly, we show how unordered as well as ordered rules can be generated. We experimentally demonstrate sig...