The many functional partnerships and interactions that occur between proteins are at the core of cellular processing and their systematic characterization helps to provide context in molecular systems biology. However, known and predicted interactions are scattered over multiple resources, and the available data exhibit notable differences in terms of quality and completeness. The STRING database (http://string-db.org) aims to provide a critical assessment and integration of protein–protein interactions, including direct (physical) as well as indirect (functional) associations. The new version 10.0 of STRING covers more than 2000 organisms, which has necessitated novel, scalable algorithms for transferring interaction information between organisms. For this purpose, we have introduced hierarchical and self-consistent orthology annotations for all interacting proteins, grouping the proteins into families at various levels of phylogenetic resolution. Further improvements in version 10.0 include a completely redesigned prediction pipeline for inferring protein–protein associations from co-expression data, an API interface for the R computing environment and improved statistical analysis for enrichment tests in user-provided networks.

AbstracteggNOG is a public database of orthology relationships, gene evolutionary histories and functional annotations. Here, we present version 5.0, featuring a major update of the underlying genome sets, which have been expanded to 4445 representative bacteria and 168 archaea derived from 25 038 genomes, as well as 477 eukaryotic organisms and 2502 viral proteomes that were selected for diversity and filtered by genome quality. In total, 4.4M orthologous groups (OGs) distributed across 379 taxonomic levels were computed together with their associated sequence alignments, phylogenies, HMM models and functional descriptors. Precomputed evolutionary analysis provides fine-grained resolution of duplication/speciation events within each OG. Our benchmarks show that, despite doubling the amount of genomes, the quality of orthology assignments and functional annotations (80% coverage) has persisted without significant changes across this update. Finally, we improved eggNOG online services for fast functional annotation and orthology prediction of custom genomics or metagenomics datasets. All precomputed data are publicly available for downloading or via API queries at http://eggnog.embl.de

eggNOG is a public resource that provides Orthologous Groups (OGs) of proteins at different taxonomic levels, each with integrated and summarized functional annotations. Developments since the latest public release include changes to the algorithm for creating OGs across taxonomic levels, making nested groups hierarchically consistent. This allows for a better propagation of functional terms across nested OGs and led to the novel annotation of 95 890 previously uncharacterized OGs, increasing overall annotation coverage from 67% to 72%. The functional annotations of OGs have been expanded to also provide Gene Ontology terms, KEGG pathways and SMART/Pfam domains for each group. Moreover, eggNOG now provides pairwise orthology relationships within OGs based on analysis of phylogenetic trees. We have also incorporated a framework for quickly mapping novel sequences to OGs based on precomputed HMM profiles. Finally, eggNOG version 4.5 incorporates a novel data set spanning 2605 viral OGs, covering 5228 proteins from 352 viral proteomes. All data are accessible for bulk downloading, as a web-service, and through a completely redesigned web interface. The new access points provide faster searches and a number of new browsing and visualization capabilities, facilitating the needs of both experts and less experienced users. eggNOG v4.5 is available at http://eggnog.embl.de.

22The collective behaviour of cells in epithelial tissues is dependent on their 23 mechanical properties. However, the contribution of tissue mechanics to wound 24 90 cell-based models, such as vertex models 26,27 , have rarely been applied to replicate 91 in vivo wound healing dynamics. We model each cell in the tissue as a two-92 dimensional polygon carrying variable tension on their edges, with bulk elasticity and 93 peripheral contractility ( Supplementary Fig. 2a-b, methods). We parameterised the 94 model so that edges contacting the wound gradually increase in tension compared to 95 5 the surrounding tissue, to mimic the assembly of the contractile actomyosin purse 96 string, causing wound edge junctions to reduce in length. To capture experimentally 97 observed fluctuations in junctional and purse-string MyoII 28 , we introduced 98 fluctuations in line tension at cell-cell interfaces and in the purse-string 99 ( Supplementary Fig. 2d). Without introducing intercalation events into the model, 100 simulated wounds are unable to close (Figs. 2a, c, Supplementary Video 3). By 101 contrast, when intercalations are enabled in the model ( Supplementary Fig. 2c, see 102 methods), wounds are able to close (Figs. 2b, d, Supplementary Video 4), supporting 103 our hypothesis that intercalations at the wound edge are necessary to drive wound 104 closure. 105The vertex model predicts that in the absence of intercalation, cells around 106 the wound become more elongated towards the centre of the wound (Fig. 2e) than in 107 simulations with intercalations enabled (Fig. 2f). In both cases, the cells initially 108 elongate as the purse-string contracts the wound. As cells begin to intercalate away 109 from the wound edge their shapes relax, reducing the elongation over time. Towards 110 the end of wound closure, many intercalations occur (Fig. 2b), at which point the 111 elongation rapidly decreases, and the cells return to a fully relaxed state after healing 112 (Fig. 2f). With intercalations disabled, the cells remain highly elongated ( Fig. 2e). 113This led us to hypothesise that wound edge intercalations play a crucial role in 114 maintaining cell shape and tissue patterning. Indeed, wing disc cells appear regularly 115 packed immediately after wound closure (Fig. 3a) and the polygon distribution of 116 wound edge cells is restored upon healing (Fig. 3b). The seamless closure we 117 observe is distinct from a number of in vivo 22,29 and in vitro 5,30 systems that can form 118 visible scar-like rosette structures upon closure. To test our vertex model's prediction 119 that intercalation preserves cell shape, we quantified cell elongation in the first three 120 6 rows of cells away from the wound in wing discs ( Fig. 3c, Supplementary Video 5).

SummaryEpithelia grow and undergo extensive rearrangements to achieve their final size and shape. Imaging the dynamics of tissue growth and morphogenesis is now possible with advances in time-lapse microscopy, but a true understanding of their complexities is limited by automated image analysis tools to extract quantitative data. To overcome such limitations, we have designed a new open-source image analysis toolkit called EpiTools. It provides user-friendly graphical user interfaces for accurately segmenting and tracking the contours of cell membrane signals obtained from 4D confocal imaging. It is designed for a broad audience, especially biologists with no computer-science background. Quantitative data extraction is integrated into a larger bioimaging platform, Icy, to increase the visibility and usability of our tools. We demonstrate the usefulness of EpiTools by analyzing Drosophila wing imaginal disc growth, revealing previously overlooked properties of this dynamic tissue, such as the patterns of cellular rearrangements.

Summary: The Quest for Orthologs (QfO) is an open collaboration framework for experts in comparative phylogenomics and related research areas who have an interest in highly accurate orthology predictions and their applications. We here report highlights and discussion points from the QfO meeting 2015 held in Barcelona. Achievements in recent years have established a basis to support developments for improved orthology prediction and to explore new approaches. Central to the QfO effort is proper benchmarking of methods and services, as well as design of standardized datasets and standardized formats to allow sharing and comparison of results. Simultaneously, analysis pipelines have been improved, evaluated and adapted to handle large datasets. All this would not have occurred without the long-term collaboration of Consortium members. Meeting regularly to review and coordinate complementary activities from a broad spectrum of innovative researchers clearly benefits the community. Highlights of the meeting include addressing sources of and legitimacy of disagreements between orthology calls, the context dependency of orthology definitions, special challenges encountered when analyzing very anciently rooted orthologies, orthology in the light of whole-genome duplications, and the concept of orthologous versus paralogous relationships at different levels, including domain-level orthology. Furthermore, particular needs for different applications (e.g. plant genomics, ancient gene families and others) and the infrastructure for making orthology inferences available (e.g. interfaces with model organism databases) were discussed, with several ongoing efforts that are expected to be reported on during the upcoming 2017 QfO meeting.

The SIB Swiss Institute of Bioinformatics (www.isb-sib.ch) provides world-class bioinformatics databases, software tools, services and training to the international life science community in academia and industry. These solutions allow life scientists to turn the exponentially growing amount of data into knowledge. Here, we provide an overview of SIB's resources and competence areas, with a strong focus on curated databases and SIB's most popular and widely used resources. In particular, SIB's Bioinformatics resource portal ExPASy features over 150 resources, including UniProtKB/Swiss-Prot, ENZYME, PROSITE, neXtProt, STRING, UniCarbKB, SugarBindDB, SwissRegulon, EPD, arrayMap, Bgee, SWISS-MODEL Repository, OMA, OrthoDB and other databases, which are briefly described in this article.

Nuclear magnetic resonance (NMR) spectroscopy together with X-ray crystallography, are the main techniques used for the determination of high-resolution 3D structures of biological molecules. The output of an NMR experiment includes a set of lower and upper limits for the distances (constraints) between pairs of atoms. If the number of constraints is high enough, there will be a finite number of possible conformations (models) of the macromolecule satisfying the data. Thus, the more constraints are measured, the better defined these structures will be. The availability of a user-friendly tool able to help in the analysis and interpretation of the number of experimental constraints per residue, is thus of valuable importance when assessing the levels of structure definition of NMR solved biological macromolecules, in particular, when high-quality structures are needed in techniques such as, computational biology approaches, site-directed mutagenesis experiments and/or drug design. Here, we present a free publicly available web-server, i.e. NMR Constraints Analyser, which is aimed at providing an automatic graphical analysis of the NMR experimental constraints atom by atom. The NMR Constraints Analyser server is available from the web-page http://molsim.sci.univr.it/constraint