MicroRNAs (miRNAs) are endogenous ∼23 nt RNAs that play important gene-regulatory roles in animals and plants by pairing to the mRNAs of protein-coding genes to direct their posttranscriptional repression. This review outlines the current understanding of miRNA target recognition in animals and discusses the widespread impact of miRNAs on both the expression and evolution of protein-coding genes.

MicroRNAs: Target Recognition and Regulatory Functions

An Empirical-Statistical Agenda for Recognition.- A Formal-Physical Agenda for Recognition.- Shape.- Shape Models and Object Recognition.- Order Structure, Correspondence, and Shape Based Categories.- Quasi-Invariant Parameterisations and Their Applications in Computer Vision.- Shading.- Representations for Recognition Under Variable Illumination.- Shadows, Shading, and Projective Ambiguity.- Grouping.- Grouping in the Normalized Cut Framework.- Geometric Grouping of Repeated Elements within Images.- Constrained Symmetry for Change Detection.- Grouping Based on Coupled Diffusion Maps.- Representation and Recognition.- Integrating Geometric and Photometric Information for Image Retrieval.- Towards the Integration of Geometric and Appearance-Based Object Recognition.- Recognizing Objects Using Color-Annotated Adjacency Graphs.- A Cooperating Strategy for Objects Recognition.- Statistics, Learning and Recognition.- Model Selection for Two View Geometry:A Review.- Finding Objects by Grouping Primitives.- Object Recognition with Gradient-Based Learning.

Shape, Contour and Grouping in Computer Vision

Microservices is an architectural style increasing in popularity. However, there is still a lack of understanding how to adopt a microservice-based architectural style. We aim at characterizing different microservice architectural style patterns and the principles that guide their definition. We conducted a systematic mapping study in order to identify reported usage of microservices and based on these use cases extract common patterns and principles. We present two key contributions. Firstly, we identified several agreed microservice architecture patterns that seem widely adopted and reported in the case studies identified. Secondly, we presented these as a catalogue in a common template format including a summary of the advantages, disadvantages, and lessons learned for each pattern from the case studies. We can conclude that different architecture patterns emerge for different migration, orchestration, storage and deployment settings for a set of agreed principles.

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Architectural Patterns for Microservices: A Systematic Mapping Study

The cloud is an emerging paradigm which leads the way for different approaches and standards. The architectural styles are evolving based on the requirements of the cloud as well. In recent years microservices is seen as the architecture style for scalable, fast evolving cloud applications. As part of this paper, a systematic mapping study was carried out around microservices. It is aiming to find out the current trends around microservices, the motivation behind microservices research, emerging standards and the possible research gaps. The obtained results can help researchers and practitioner in software engineering domain who want to be aware of new trends about SOA and cloud computing.

A Systematic Literature Review on Microservices

A dataflow-driven approach to identifying microservices from monolithic applications

Monolithic applications are the most common development paradigm but they have some drawback related to the maintenance, upgrading and scaling. Microservice architectures were recently proposed in order to solve some of these issues, because they are simpler to scale and more flexible. Both architectures use a database and this component can act as a component for micro service. In the paper we present a pattern for microservice architecture that uses a database as component, and this pattern is used in an health record application. We explain also the requirements of the database for this pattern and the advantages achieved.

The Database-is-the-Service Pattern for Microservice Architectures

Several online databases provide a large amount of biomedical data of different biological entities. These resources are typically stored in systems implementing their own data model, user interface and query language. On the other hand, in many bioinformatics scenarios there is often the need to use more than one resource. The availability of a single bioinformatics platform that integrates many biological resources and services is, for those reasons a fundamental issue. Here, we present BioGraph, a web application that allows to query, visualize and analyze biological data belonging to several online available sources. BioGraph is built upon our previously developed graph database called BioGraphDB, that integrates and stores heterogeneous biological resources and make them available by means of a common structure and a unique query language. BioGraph implements state-of-the-art technologies and provides pre-compiled bioinformatics scenarios, as well as the possibility to perform custom queries and obtaining an interactive and dynamic visualization of results. We present a case study about functional analysis of microRNA in breast cancer in order to demonstrate the functionalities of the system. BioGraph is freely available at http://biograph.pa.icar.cnr.it
 . Source files are available on GitHub at https://github.com/IcarPA-TBlab/BioGraph

/pdf/biograph-a-web-application-and-a-graph-database-for-querying-4bev246j7z.pdf

BioGraph: a web application and a graph database for querying and analyzing bioinformatics resources

The proliferation of biological research data generated and shared openly online is of huge benefit to the scientific community, but there are often significant challenges to overcome before it can be integrated from different sources and re-used to gain new knowledge. This paper introduces BioGrakn, which is a graph-based deductive database, combining the power of knowledge graphs and machine reasoning. BioGrakn illustrates how data can be aggregated and integrated, modelled in all its complexity and contextual specificity, and extended as needed. Built upon GRAKN.AI, it provides an integrated, intelligent database for researchers handling complex data.

BioGrakn: A Knowledge Graph-Based Semantic Database for Biomedical Sciences

Distributed perceptual systems are endowed with different kind of sensors, from which information flows to suitable modules to perform useful elaborations for decisions making. In this paper a new distributed architecture, named "Distributed Architecture for Intelligent SYstem" (DAISY), is proposed. It is based on the concept of co-operating behavioral agents supervised by a "Central Engagement Module". This module integrates the processing of data coming from the behavioral agents with a symbolic level of representation, by the introduction of a "conceptual space" intermediate analogue representation. The DAISY project is under development; experiments on navigation and exploration for an autonomous robot are done to evaluate its performance.

DAISY: a distributed architecture for intelligent system

IT complexity in enterprise today continues to grow at a dizzying rate. Technology innovation, vendor heterogeneity, and business demands are major reasons why organizations are exposed to new risks, based on the gaps opened between the options and features of each IT element and product, and how they are implemented to support a well-defined policy and company strategy. Moreover, the impact of such risks is exacerbated exponentially by failing to identify the handshakes and correlations of interrelated elements. Products, vendors, and IT layers, must work in tandem to prevent potential "black holes": risks related to availability, resiliency and data loss. In this paper, we propose a possible approach to reduce complexity, and thus the related risks, and also to gain improvements in terms of simplicity, speed and scalability. In order to achieve those objectives, we can add new behaviors and a business logic at the database level, if easily obtainable. We did it with OrientDB, a Multi-Model NoSQL database, through the development of native extensions, such as the XML-over-SOAP service study case.

Antonio Messina

Papers

The Database-is-the-Service Pattern for Microservice Architectures

BioGraph: a web application and a graph database for querying and analyzing bioinformatics resources

BioGrakn: A Knowledge Graph-Based Semantic Database for Biomedical Sciences

DAISY: a distributed architecture for intelligent system

Keep It Simple, Fast and Scalable: A Multi-model NoSQL DBMS as an (eb) XML-over-SOAP Service