Abstract. A coupled cell network describes interacting (coupled) individual systems (cells). As in networks from real applications, coupled cell networks can represent inhomogeneous networks where different types of cells interact with each other in different ways, which can be represented graphically by different symbols, or abstractly by equivalence relations.Various synchronous behaviors, from full synchrony to partial synchrony, can be observed for a given network. Patterns of synchrony, which do not depend on specific dynamics of the network, but only on the network structure, are associated with a special type of partition of cells, termed balanced equivalence relations. Algorithms in Aldis (2008) and Belykh and Hasler (2011) find the unique pattern of synchrony with the least clusters. In this paper, we compute the set of all possible patterns of synchrony and show their hierarchy structure as a complete lattice.We represent the network structure of a given coupled cell network by a symbolic adjacency matrix encoding the different coupling types. We show that balanced equivalence relations can be determined by a matrix computation on the adjacency matrix which forms a block structure for each balanced equivalence relation. This leads to a computer algorithm to search for all possible balanced equivalence relations. Our computer program outputs the balanced equivalence relations, quotient matrices, and a complete lattice for user specified coupled cell networks. Finding the balanced equivalence relations of any network of up to 15 nodes is tractable, but for larger networks this depends on the pattern of synchrony with least clusters.

Background: The NCBI BLAST suite has become ubiquitous in modern molecular biology and is used for small tasks such as checking capillary sequencing results of single PCR products, genome annotation or even larger scale pan-genome analyses. For early adopters of the Galaxy web-based biomedical data analysis platform, integrating BLAST into Galaxy was a natural step for sequence comparison workflows. Findings: The command line NCBI BLAST+ tool suite was wrapped for use within Galaxy. Appropriate datatypes were defined as needed. The integration of the BLAST+ tool suite into Galaxy has the goal of making common BLAST tasks easy and advanced tasks possible. Conclusions: This project is an informal international collaborative effort, and is deployed and used on Galaxy servers worldwide. Several examples of applications are described here.

While the majority of Aphelenchoides species are fungivorous, some species are plant parasites that have retained the ability to feed on fungi. Aphelenchoides besseyi is an important and widespread pathogen that causes 'white tip' disease on rice. This migratory endoparasitic nematode makes a significant contribution to the estimated SUS 16 billion worth of damage caused by nematodes to rice crops. Here we describe a small-scale analysis of the transcriptome of A. besseyi. After sequencing, QC and assembly, approximately 5000 contigs were analysed. Bioinformatic analysis allowed 375 secreted proteins to be identified, including orthologues of proteins known to be secreted by other nematodes. One contig could encode an A. besseyi orthologue of a GHF45 cellulase, similar to those present in Bursaphelenchus xylophilus. No transcripts similar to GHF5 cellulases were present in this dataset.

Repositories: The RNA sequences of 2 raspberry plants exhibiting virus-like symptoms have been deposited in the European Nucleotide Archive and assigned accessions ERR2784286 (D5) and ERR2784287(D6)

Background Nucleotide and protein sequence feature annotations are essential to understand biology on the