The latest book on Genetic Programming, Poli, Langdon and McPhee's (with contributions
from John R. Koza) A Field Guide to Genetic Programming represents an exciting landmark …

The rapid advancements in high-throughput techniques have fueled large-scale production
of biological data at very affordable costs. Some of these techniques are microarrays and …

When modeling cell signaling networks, a balance must be struck between mechanistic
detail and ease of interpretation. In this paper we apply a fuzzy logic framework to the …

The goal of having computers automatically solve problems is central to artificial
intelligence, machine learning, and the broad area encompassed by what Turing called …

In order to reconstruct large-scale gene regulatory networks (GRNs) with high accuracy, a
robust evolutionary algorithm, a dynamic multiagent genetic algorithm (dMAGA), is proposed …

Classification is an important data mining task that widely used in several different real world
applications. In microarray analysis, classification techniques are applied in order to …

Recent analysis of single-cell transcriptomic data has revealed a surprising organization of
the transcriptional variability pervasive across individual neurons. In response to distinct …

Background Expert knowledge in journal articles is an important source of data for
reconstructing biological pathways and creating new hypotheses. An important need for …

Sažetak In this paper, the publicly available dataset of condition based maintenance of
combined diesel-electric and gas (CODLAG) propulsion system for ships has been utilized …

Recently, many methods have been proposed for constructing gene regulatory networks
(GRNs). However, most of the existing methods ignored the time delay regulatory relation in …