Revisiting the Edge of Chaos: Evolving Cellular Automata to Perform Computations

We present results from an experiment similar to one performed by Packard (1988), in which a genetic algorithm is used to evolve cellular automata (CA) to perform a particular computational task. Packard examined the frequency of evolved CA rules as a function of Langton's lambda parameter (Langton, 1990), and interpreted the results of his experiment as giving evidence for the following two hypotheses: (1) CA rules able to perform complex computations are most likely to be found near ``critical'' lambda values, which have been claimed to correlate with a phase transition between ordered and chaotic behavioral regimes for CA; (2) When CA rules are evolved to perform a complex computation, evolution will tend to select rules with lambda values close to the critical values. Our experiment produced very different results, and we suggest that the interpretation of the original results is not correct. We also review and discuss issues related to lambda, dynamical-behavior classes, and computation in CA. The main constructive results of our study are identifying the emergence and competition of computational strategies and analyzing the central role of symmetries in an evolutionary system. In particular, we demonstrate how symmetry breaking can impede the evolution toward higher computational capability.Comment: 38 pages, compressed .ps files (780Kb) available ONLY thru anonymous ftp. (Instructions available via `get 9303003' .

Left and right brain hemispheres and their effect on creativity

None provided

Comparative analysis of hepatitis C virus phylogenies from coding and non-coding regions: the 5' untranslated region (UTR) fails to classify subtypes

BACKGROUND: The duration of treatment for HCV infection is partly indicated by the genotype of the virus. For studies of disease transmission, vaccine design, and surveillance for novel variants, subtype-level classification is also needed. This study used the Shimodaira-Hasegawa test and related statistical techniques to compare phylogenetic trees obtained from coding and non-coding regions of a whole-genome alignment for the reliability of subtyping in different regions. RESULTS: Different regions of the HCV genome yield inconsistent phylogenies, which can lead to erroneous conclusions about classification of a given infection. In particular, the highly conserved 5' untranslated region (UTR) yields phylogenetic trees with topologies that differ from the HCV polyprotein and complete genome phylogenies. Phylogenetic trees from the NS5B gene reliably cluster related subtypes, and yield topologies consistent with those of the whole genome and polyprotein. CONCLUSION: These results extend those from previous studies and indicate that, unlike the NS5B gene, the 5' UTR contains insufficient variation to resolve HCV classifications to the level of viral subtype, and fails to distinguish genotypes reliably. Use of the 5' UTR for clinical tests to characterize HCV infection should be replaced by a subtype-informative test

jpHMM: Improving the reliability of recombination prediction in HIV-1

Previously, we developed jumping profile hidden Markov model (jpHMM), a new method to detect recombinations in HIV-1 genomes. The jpHMM predicts recombination breakpoints in a query sequence and assigns to each position of the sequence one of the major HIV-1 subtypes. Since incorrect subtype assignment or recombination prediction may lead to wrong conclusions in epidemiological or vaccine research, information about the reliability of the predicted parental subtypes and breakpoint positions is valuable. For this reason, we extended the output of jpHMM to include such information in terms of ‘uncertainty’ regions in the recombination prediction and an interval estimate of the breakpoint. Both types of information are computed based on the posterior probabilities of the subtypes at each query sequence position. Our results show that this extension strongly improves the reliability of the jpHMM recombination prediction. The jpHMM is available online at http://jphmm.gobics.de/

ORION-VIRCAT: a tool for mapping ICTV and NCBI taxonomies

Viruses, viroids and prions are the smallest infectious biological entities that depend on their host for replication. The number of pathogenic viruses is considerably large and their impact in human global health is well documented. Currently, the International Committee on the Taxonomy of Viruses (ICTV) has classified ∼4379 virus species while the National Center for Biotechnology Information Viral Genomes Resource (NCBI-VGR) database has mapped 617 705 proteins to eight large taxonomic groups. Despite these efforts, an automated approach for mapping the ICTV master list and its officially accepted virus naming to the NCBI-VGR’s taxonomical classification is not available. Due to metagenomic sequencing, it is likely that the discovery and naming of new viral species will increase by at least ten fold. Unfortunately, existing viral databases are not adequately prepared to scale, maintain and annotate automatically ultra-high throughput sequences and place this information into specific taxonomic categories. ORION-VIRCAT is a scalable and interoperable object-relational database designed to serve as a resource for the integration and verification of taxonomical classifications generated by the ICTV and NCBI-VGR. The current release (v1.0) of ORION-VIRCAT is implemented in PostgreSQL and it has been extended to ORACLE, MySQL and SyBase. ORION-VIRCAT automatically mapped and joined 617 705 entries from the NCBI-VGR to the viral naming of the ICTV. This detailed analysis revealed that 399 095 entries from the NCBI-VGR can be mapped to the ICTV classification and that one Order, 10 families, 35 genera and 503 species listed in the ICTV disagree with the the NCBI-VGR classification schema. Nevertheless, we were eable to correct several discrepancies mapping 234 000 additional entries