Concept: Software architecture
- Database : the journal of biological databases and curation
- Published almost 3 years ago
Galaxy is a popular framework for execution of complex analytical pipelines typically for large data sets, and is a commonly used for (but not limited to) genomic, genetic and related biological analysis. It provides a web front-end and integrates with high performance computing resources. Here we report the development of the blend4php library that wraps Galaxy’s RESTful API into a PHP-based library. PHP-based web applications can use blend4php to automate execution, monitoring and management of a remote Galaxy server, including its users, workflows, jobs and more. The blend4php library was specifically developed for the integration of Galaxy with Tripal, the open-source toolkit for the creation of online genomic and genetic web sites. However, it was designed as an independent library for use by any application, and is freely available under version 3 of the GNU Lesser General Public License (LPGL v3.0) at https://github.com/galaxyproject/blend4phpDatabase URL: https://github.com/galaxyproject/blend4php.
To deal with the large number of malicious mobile applications (e.g. mobile malware), a number of malware detection systems have been proposed in the literature. In this paper, we propose a hybrid method to find the optimum parameters that can be used to facilitate mobile malware identification. We also present a multi agent system architecture comprising three system agents (i.e. sniffer, extraction and selection agent) to capture and manage the pcap file for data preparation phase. In our hybrid approach, we combine an adaptive neuro fuzzy inference system (ANFIS) and particle swarm optimization (PSO). Evaluations using data captured on a real-world Android device and the MalGenome dataset demonstrate the effectiveness of our approach, in comparison to two hybrid optimization methods which are differential evolution (ANFIS-DE) and ant colony optimization (ANFIS-ACO).
Integration of responses within and across Arabidopsis natural accessions uncovers loci controlling root systems architecture
- Proceedings of the National Academy of Sciences of the United States of America
- Published over 6 years ago
Phenotypic plasticity is presumed to be involved in adaptive change toward species diversification. We thus examined how candidate genes underlying natural variation across populations might also mediate plasticity within an individual. Our implementation of an integrative “plasticity space” approach revealed that the root plasticity of a single Arabidopsis accession exposed to distinct environments broadly recapitulates the natural variation “space.” Genome-wide association mapping identified the known gene PHOSPHATE 1 (PHO1) and other genes such as Root System Architecture 1 (RSA1) associated with differences in root allometry, a highly plastic trait capturing the distribution of lateral roots along the primary axis. The response of mutants in the Columbia-0 background suggests their involvement in signaling key modulators of root development including auxin, abscisic acid, and nitrate. Moreover, genotype-by-environment interactions for the PHO1 and RSA1 genes in Columbia-0 phenocopy the root allometry of other natural variants. This finding supports a role for plasticity responses in phenotypic evolution in natural environments.
The meta-ecosystem framework demonstrates the significance of among-ecosystem spatial flows for ecosystem dynamics and has fostered a rich body of theory. The high level of abstraction of the models, however, impedes applications to empirical systems. We argue that further understanding of spatial dynamics in natural systems strongly depends on dense exchanges between field and theory. From empiricists, more and specific quantifications of spatial flows are needed, defined by the major categories of organismal movement (dispersal, foraging, life-cycle, and migration). In parallel, the theoretical framework must account for the distinct spatial scales at which these naturally common spatial flows occur. Integrating all levels of spatial connections among landscape elements will upgrade and unify landscape and meta-ecosystem ecology into a single framework for spatial ecology.
AMPA-type glutamate receptors (AMPARs), central mediators of rapid neurotransmission and synaptic plasticity, predominantly exist as heteromers of the GluA1-4 subunits. Here we report first AMPAR heteromer structures, which deviate substantially from existing GluA2 homomers. Crystal structures of the GluA2/3 and GluA2/4 N-terminal domains reveal a novel compact conformation with an alternating arrangement of the four subunits around a central axis. This organization is confirmed by cysteine crosslinking in full-length receptors and permitted us to determine the structure of an intact GluA2/3 receptor by cryo-EM. Two models in the ligand-free state, at 8.25 Å and 10.3 Å resolution, exhibit a substantial vertical compression and close associations between domain layers, reminiscent of NMDA receptors. Model 1 resembles a resting state, model 2 a desensitized state, providing snapshots of gating transitions in the nominal absence of ligand. Our data reveal organizational features of heteromeric AMPARs and provide a framework to decipher AMPAR architecture and signaling.
Data abstraction is a key step in conducting systematic reviews because data collected from study reports form the basis of appropriate conclusions. Recent methodological standards and expectations highlight several principles for data collection. To support implementation of these standards, this article provides a step-by-step tutorial for selecting data collection tools; constructing data collection forms; and abstracting, managing, and archiving data for systematic reviews. Examples are drawn from recent experience using the Systematic Review Data Repository for data collection and management. If it is done well, data collection for systematic reviews only needs to be done by 1 team and placed into a publicly accessible database for future use. Technological innovations, such as the Systematic Review Data Repository, will contribute to finding trustworthy answers for many health and health care questions.
The kitchen environment is one of the scenarios in the home where users can benefit from Ambient Assisted Living (AAL) applications. Moreover, it is the place where old people suffer from most domestic injuries. This paper presents a novel design, implementation and assessment of a Smart Kitchen which provides Ambient Assisted Living services; a smart environment that increases elderly and disabled people’s autonomy in their kitchen-related activities through context and user awareness, appropriate user interaction and artificial intelligence. It is based on a modular architecture which integrates a wide variety of home technology (household appliances, sensors, user interfaces, etc.) and associated communication standards and media (power line, radio frequency, infrared and cabled). Its software architecture is based on the Open Services Gateway initiative (OSGi), which allows building a complex system composed of small modules, each one providing the specific functionalities required, and can be easily scaled to meet our needs. The system has been evaluated by a large number of real users (63) and carers (31) in two living labs in Spain and UK. Results show a large potential of system functionalities combined with good usability and physical, sensory and cognitive accessibility.
To address the impending need for exploring rapidly increased transcriptomics data generated for non-model organisms, we developed CBrowse, an AJAX-based web browser for visualizing and analyzing transcriptome assemblies and contigs. Designed in a standard three-tier architecture with a data pre-processing pipeline, CBrowse is essentially a Rich Internet Application that offers many seamlessly integrated web interfaces and allows users to navigate, sort, filter, search and visualize data smoothly. The pre-processing pipeline takes the contig sequence file in FASTA format and its relevant SAM/BAM file as the input; detects putative polymorphisms, simple sequence repeats and sequencing errors in contigs and generates image, JSON and database-compatible CSV text files that are directly utilized by different web interfaces. CBowse is a generic visualization and analysis tool that facilitates close examination of assembly quality, genetic polymorphisms, sequence repeats and/or sequencing errors in transcriptome sequencing projects.
In several disciplines, identifying relevant root traits to characterize the root system architecture of species or genotypes is a crucial step. To address this question, we analysed the inter-specific variations of root architectural traits in two contrasting environments.