Enhancing metagenomic classification with compression-based features.

Metagenomics is a rapidly expanding field that uses next-generation sequencing technology to analyze the genetic makeup of environmental samples. However, accurately identifying the organisms in a metagenomic sample can be complex, and traditional reference-based methods may need to be more effective in some instances. In this study, we present a novel approach for metagenomic identification, using data compressors as a feature for taxonomic classification.

Characterizing Genomics Repositories Using Feature-Based Classification.

In the last decades, the field of metagenomics aided by NGS technologies has grown exponentially and is now a cornerstone tool in medicine. However, even with the current technologies, obtaining a conclusive identification of an organism can be challenging due to using reference-based methods. Consequently, when releasing a new repository of genomic data that contains de-novo sequences, it is problematic to characterize its content.

The complexity landscape of viral genomes.

Background: Viruses are among the shortest yet highly abundant species that harbor minimal instructions to infect cells, adapt, multiply, and exist. However, with the current substantial availability of viral genome sequences, the scientific repertory lacks a complexity landscape that automatically enlights viral genomes' organization, relation, and fundamental characteristics.

Results: This work provides a comprehensive landscape of the viral genome's complexity (or quantity of information), identifying the most redundant and complex groups regarding their genome sequence while providing their distribution and characteristics at a large and local scale.

SCREEN-DR: Collaborative platform for diabetic retinopathy.

Background And Objective: Diabetic retinopathy (DR) is the most prevalent microvascular complication of diabetes mellitus and can lead to irreversible visual loss. Screening programs, based on retinal imaging techniques, are fundamental to detect the disease since the initial stages are asymptomatic. Most of these examinations reflect negative cases and many have poor image quality, representing an important inefficiency factor.

SCREEN-DR - Software Architecture for the Diabetic Retinopathy Screening.

Diabetic Retinopathy (DR) is a common complication of diabetes that may lead to blindness if not treated. However, since DR evolves without any symptoms in the initial stages, early detection and treatment can only be achieved through routine checks. This article presents the collaborative platform of the SCREEN-DR project that promotes partnership between physicians and researchers in the scope of a regional DR screening program.

Controlled searching in reversibly de-identified medical imaging archives.

Nowadays, digital medical imaging in healthcare has become a fundamental tool for medical diagnosis. This growth has been accompanied by the development of technologies and standards, such as the DICOM standard and PACS. This environment led to the creation of collaborative projects where there is a need to share medical data between different institutions for research and educational purposes.

Web Validation Service for Ensuring Adherence to the DICOM Standard.

The DICOM Standard has been fundamental for ensuring the interoperability of Picture Archive and Communications Systems (PACS). By compiling rigorously to the standard, medical imaging equipment and applications from different vendors can share their data, and create integrated workflows which contributes to better quality healthcare services. However, DICOM is a complex, flexible and very extensive standard.