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The RepeatsDB database (URL: https://repeatsdb.org/) provides annotations and classification for protein tandem repeat structures from the Protein Data Bank (PDB). Protein tandem repeats are ubiquitous in all branches of the tree of life. The accumulation of solved repeat structures provides new possibilities for classification and detection, but also increasing the need for annotation. Here we present RepeatsDB 3.0, which addresses these challenges and presents an extended classification scheme. The major conceptual change compared to the previous version is the hierarchical classification combining top levels based solely on structural similarity (Class > Topology > Fold) with two new levels (Clan > Family) requiring sequence similarity and describing repeat motifs in collaboration with Pfam. Data growth has been addressed with improved mechanisms for browsing the classification hierarchy. A new UniProt-centric view unifies the increasingly frequent annotation of structures from identical or similar sequences. This update of RepeatsDB aligns with our commitment to develop a resource that extracts, organizes and distributes specialized information on tandem repeat protein structures., Facultad de Ciencias Exactas, Instituto de Biotecnologia y Biologia Molecular

Resolución de problemas usando Visual Basic for Applications en Excel presenta las herramientas y los métodos de lenguaje VBA en Excel y los emplea de manera didáctica mediante la propuesta y el desarrollo de ejercicios de aplicación. De esta manera, el libro permite a los estudiantes de cursos introductorios de informática y en general a usuarios avanzados en Excel aproximarse al proceso de resolución de problemas en ese programa de forma sencilla y directa.

The programing languages are classified by its paradigms, some paradigms are easier to understand than others, or at least we have that impression. But when we learn our first language, what paradigm is the best? Many people could say that structured is better, because is a recipe to follow, or maybe an object oriented, because it-s a natural definition, others could say that functional is better. Actually the debate of which should be the first language to learn is growing, and it will continue growing. Nowadays we decide which language to learn as a result of a necessity, more than analyse which one is easier to understand or which should be the correct learning process. This paper will present a tool in Spanish that could be used as an instrument to understand these concepts of object oriented and its management before starting the programming. KEYWORDS IDE, Object Oriented Programming, language For More Details: https://wireilla.com/papers/ijpla/V3N3/3313ijpla02.pdf

Conformational changes in RNA native ensembles are central to fulfill many of their biological roles. Systematic knowledge of the extent and possible modulators of this conformational diversity is desirable to better understand the relationship between RNA dynamics and function.We have developed CoDNaS-RNA as the first database of conformational diversity in RNA molecules. Known RNA structures are retrieved and clustered to identify alternative conformers of each molecule. Pairwise structural comparisons within each cluster allows to measure the variability of the molecule. Additional data on structural features, molecular interactions and functional annotations are provided. CoDNaS-RNA is implemented as a public resource that can be of much interest for computational and bench scientists alike.AvailabilityCoDNaS-RNA is freely accessible at http://ufq.unq.edu.ar/codnasrnaContactnpalopoli@unq.edu.ar

Revenant is a database of resurrected proteins coming from extinct organisms. Currently, it contains a manually curated collection of 84 resurrected proteins derived from bibliographic data. Each protein is extensively annotated, including structural, biochemical and biophysical information. Revenant contains a browse capability designed as a timeline from where the different proteins can be accessed. The oldest Revenant entries are between 4200 and 3500 million years ago, while the younger entries are between 8.8 and 6.3 million years ago. These proteins have been resurrected using computational tools called ancestral sequence reconstruction techniques combined with wet-laboratory synthesis and expression. Resurrected proteins are commonly used, with a noticeable increase during the past years, to explore and test different evolutionary hypotheses such as protein stability, to explore the origin of new functions, to get biochemical insights into past metabolisms and to explore specificity and promiscuous behaviour of ancient proteins.

The programing languages are classified by its paradigms, some paradigms are easier to understand than others, or at least we have that impression. But when we learn our first language, what paradigm is the best? Many people could say that structured is better, because is a recipe to follow, or maybe an object oriented, because it-s a natural definition, others could say that functional is better. Actually the debate of which should be the first language to learn is growing, and it will continue growing. Nowadays we decide which language to learn as a result of a necessity, more than analyse which one is easier to understand or which should be the correct learning process. This paper will present a tool in Spanish that could be used as an instrument to understand these concepts of object oriented and its management before starting the programming.

Over the last decade, numerous studies have demonstrated the fundamental importance of tandem repeat (TR) proteins in many biological processes. A plethora of new repeat structures have also been solved. The recently published RepeatsDB provides information on TR proteins. However, a detailed structural characterization of repetitive elements is largely missing, as repeat unit annotation is manually curated and currently covers only 3 % of the bona fide TR proteins. Repeat Protein Unit Predictor (ReUPred) is a novel method for the fast automatic prediction of repeat units and repeat classification using an extensive Structure Repeat Unit Library (SRUL) derived from RepeatsDB. ReUPred uses an iterative structural search against the SRUL to find repetitive units. On a test set of solenoid proteins, ReUPred is able to correctly detect 92 % of the proteins. Unlike previous methods, it is also able to correctly classify solenoid repeats in 89 % of cases. It also outperforms two recent state-of-the-art methods for the repeat unit identification problem. The accurate prediction of repeat units increases the number of annotated repeat units by an order of magnitude compared to the sequence-based Pfam classification. ReUPred is implemented in Python for Linux and freely available from the URL: http://protein.bio.unipd.it/reupred/ .

RepeatsDB 2.0 (URL: http://repeatsdb.bio.unipd.it/) is an update of the database of annotated tandem repeat protein structures. Repeat proteins are a widespread class of non-globular proteins carrying heterogeneous functions involved in several diseases. Here we provide a new version of RepeatsDB with an improved classification schema including high quality annotations for ∼5400 protein structures. RepeatsDB 2.0 features information on start and end positions for the repeat regions and units for all entries. The extensive growth of repeat unit characterization was possible by applying the novel ReUPred annotation method over the entire Protein Data Bank, with data quality is guaranteed by an extensive manual validation for >60% of the entries. The updated web interface includes a new search engine for complex queries and a fully re-designed entry page for a better overview of structural data. It is now possible to compare unit positions, together with secondary structure, fold information and Pfam domains. Moreover, a new classification level has been introduced on top of the existing scheme as an independent layer for sequence similarity relationships at 40%, 60% and 90% identity.

The main objective of this article is to have a clear idea of how Medical Records are currently managed and pose some basic considerations for their management that could be taken into account in developing future management systems.