Genome3D: integrating a collaborative data pipeline to expand the depth and breadth of consensus protein structure annotation.

Genome3D (https://www.genome3d.eu) is a freely available resource that provides consensus structural annotations for representative protein sequences taken from a selection of model organisms. Since the last NAR update in 2015, the method of data submission has been overhauled, with annotations now being 'pushed' to the database via an API. As a result, contributing groups are now able to manage their own structural annotations, making the resource more flexible and maintainable. The new submission protocol brings a number of additional benefits including: providing instant validation of data and avoiding the requirement to synchronise releases between resources. It also makes it possible to implement the submission of these structural annotations as an automated part of existing internal workflows. In turn, these improvements facilitate Genome3D being opened up to new prediction algorithms and groups. For the latest release of Genome3D (v2.1), the underlying dataset of sequences used as prediction targets has been updated using the latest reference proteomes available in UniProtKB. A number of new reference proteomes have also been added of particular interest to the wider scientific community: cow, pig, wheat and mycobacterium tuberculosis. These additions, along with improvements to the underlying predictions from contributing resources, has ensured that the number of annotations in Genome3D has nearly doubled since the last NAR update article. The new API has also been used to facilitate the dissemination of Genome3D data into InterPro, thereby widening the visibility of both the annotation data and annotation algorithms

PDBe: towards reusable data delivery infrastructure at protein data bank in Europe

© 2017 The Authors. Published by OUP. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1093/nar/gkx1070The Protein Data Bank in Europe (PDBe, pdbe.org) is actively engaged in the deposition, annotation, remediation, enrichment and dissemination of macromolecular structure data. This paper describes new developments and improvements at PDBe addressing three challenging areas: data enrichment, data dissemination and functional reusability. New features of the PDBe Web site are discussed, including a context dependent menu providing links to raw experimental data and improved presentation of structures solved by hybrid methods. The paper also summarizes the features of the LiteMol suite, which is a set of services enabling fast and interactive 3D visualization of structures, with associated experimental maps, annotations and quality assessment information. We introduce a library of Web components which can be easily reused to port data and functionality available at PDBe to other services. We also introduce updates to the SIFTS resource which maps PDB data to other bioinformatics resources, and the PDBe REST API.Wellcome Trust [104948]; UK Biotechnology and Biological Sciences Research Council [BB/M011674/1, BB/N019172/1, BB/M020347/1]; European Union [284209]; European Molecular Biology Laboratory (EMBL). Funding for open access charge: EMBL.Published versio

The InterPro protein families and domains database: 20 years on

The InterPro database (https://www.ebi.ac.uk/interpro/) provides an integrative classification of protein sequences into families, and identifies functionally important domains and conserved sites. InterProScan is the underlying software that allows protein and nucleic acid sequences to be searched against InterPro's signatures. Signatures are predictive models which describe protein families, domains or sites, and are provided by multiple databases. InterPro combines signatures representing equivalent families, domains or sites, and provides additional information such as descriptions, literature references and Gene Ontology (GO) terms, to produce a comprehensive resource for protein classification. Founded in 1999, InterPro has become one of the most widely used resources for protein family annotation. Here, we report the status of InterPro (version 81.0) in its 20th year of operation, and its associated software, including updates to database content, the release of a new website and REST API, and performance improvements in InterProScan

InterPro in 2019: improving coverage, classification and access to protein sequence annotations

The InterPro database (http://www.ebi.ac.uk/interpro/) classifies protein sequences into families and predicts the presence of functionally important domains and sites. Here, we report recent developments with InterPro (version 70.0) and its associated software, including an 18% growth in the size of the database in terms on new InterPro entries, updates to content, the inclusion of an additional entry type, refined modelling of discontinuous domains, and the development of a new programmatic interface and website. These developments extend and enrich the information provided by InterPro, and provide greater flexibility in terms of data access. We also show that InterPro's sequence coverage has kept pace with the growth of UniProtKB, and discuss how our evaluation of residue coverage may help guide future curation activities

The sense of smell, its signalling pathways, and the dichotomy of cilia and microvilli in olfactory sensory cells

Smell is often regarded as an ancillary perception in primates, who seem so dominated by their sense of vision. In this paper, we will portray some aspects of the significance of olfaction to human life and speculate on what evolutionary factors contribute to keeping it alive. We then outline the functional architecture of olfactory sensory neurons and their signal transduction pathways, which are the primary detectors that render olfactory perception possible. Throughout the phylogenetic tree, olfactory neurons, at their apical tip, are either decorated with cilia or with microvilli. The significance of this dichotomy is unknown. It is generally assumed that mammalian olfactory neurons are of the ciliary type only. The existance of so-called olfactory microvillar cells in mammals, however, is well documented, but their nature remains unclear and their function orphaned. This paper discusses the possibility, that in the main olfactory epithelium of mammals ciliated and microvillar sensory cells exist concurrently. We review evidence related to this hypothesis and ask, what function olfactory microvillar cells might have and what signalling mechanisms they use

Wize Mirror - a smart, multisensory cardio-metabolic risk monitoring system

In the recent years personal health monitoring systems have been gaining popularity, both as a result of the pull from the general population, keen to improve well-being and early detection of possibly serious health conditions and the push from the industry eager to translate the current significant progress in computer vision and machine learning into commercial products. One of such systems is the Wize Mirror, built as a result of the FP7 funded SEMEOTICONS (SEMEiotic Oriented Technology for Individuals CardiOmetabolic risk self-assessmeNt and Self-monitoring) project. The project aims to translate the semeiotic code of the human face into computational descriptors and measures, automatically extracted from videos, multispectral images, and 3D scans of the face. The multisensory platform, being developed as the result of that project, in the form of a smart mirror, looks for signs related to cardio-metabolic risks. The goal is to enable users to self-monitor their well-being status over time and improve their life-style via tailored user guidance. This paper is focused on the description of the part of that system, utilising computer vision and machine learning techniques to perform 3D morphological analysis of the face and recognition of psycho-somatic status both linked with cardio-metabolic risks. The paper describes the concepts, methods and the developed implementations as well as reports on the results obtained on both real and synthetic datasets

PDBe: improved findability of macromolecularstructure data in the PDB

© 2019 The Authors. Published by OUP. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1093/nar/gkz990The Protein Data Bank in Europe (PDBe), a founding member of the Worldwide Protein Data Bank (wwPDB), actively participates in the deposition, curation, validation, archiving and dissemination of macromolecular structure data. PDBe supports diverse research communities in their use of macromolecular structures by enriching the PDB data and by providing advanced tools and services for effective data access, visualization and analysis. This paper details the enrichment of data at PDBe, including mapping of RNA structures to Rfam, and identification of molecules that act as cofactors. PDBe has developed an advanced search facility with ∼100 data categories and sequence searches. New features have been included in the LiteMol viewer at PDBe, with updated visualization of carbohydrates and nucleic acids. Small molecules are now mapped more extensively to external databases and their visual representation has been enhanced. These advances help users to more easily find and interpret macromolecular structure data in order to solve scientific problems.The Protein Data Bank in Europe is supported by European Molecular Biology Laboratory-European Bioinformatics Institute; Wellcome Trust [104948]; Biotechnology and Biological Sciences Research Council [BB/N019172/1, BB/G022577/1, BB/J007471/1, BB/K016970/1, BB/K020013/1, BB/M013146/1, BB/M011674/1, BB/M020347/1, BB/M020428/1, BB/P024351/1]; European Union [284209]; ELIXIR and Open Targets. Funding for open access charge: EMB

Comparative analysis of neural transcriptomes and functional implication of unannotated intronic expression

<p>Abstract</p> <p>Background</p> <p>The transcriptome and its regulation bridge the genome and the phenome. Recent RNA-seq studies unveiled complex transcriptomes with previously unknown transcripts and functions. To investigate the characteristics of neural transcriptomes and possible functions of previously unknown transcripts, we analyzed and compared nine recent RNA-seq datasets corresponding to tissues/organs ranging from stem cell, embryonic brain cortex to adult whole brain.</p> <p>Results</p> <p>We found that the neural and stem cell transcriptomes share global similarity in both gene and chromosomal expression, but are quite different from those of liver or muscle. We also found an unusually high level of unannotated expression in mouse embryonic brains. The intronic unannotated expression was found to be strongly associated with genes annotated for neurogenesis, axon guidance, negative regulation of transcription, and neural transmission. These functions are the hallmarks of the late embryonic stage cortex, and crucial for synaptogenesis and neural circuit formation.</p> <p>Conclusions</p> <p>Our results revealed unique global and local landscapes of neural transcriptomes. It also suggested potential functional roles for previously unknown transcripts actively expressed in the developing brain cortex. Our findings provide new insights into potentially novel genes, gene functions and regulatory mechanisms in early brain development.</p

PDBe-KB: a community-driven resource for structural and functional annotations.

The Protein Data Bank in Europe-Knowledge Base (PDBe-KB, https://pdbe-kb.org) is a community-driven, collaborative resource for literature-derived, manually curated and computationally predicted structural and functional annotations of macromolecular structure data, contained in the Protein Data Bank (PDB). The goal of PDBe-KB is two-fold: (i) to increase the visibility and reduce the fragmentation of annotations contributed by specialist data resources, and to make these data more findable, accessible, interoperable and reusable (FAIR) and (ii) to place macromolecular structure data in their biological context, thus facilitating their use by the broader scientific community in fundamental and applied research. Here, we describe the guidelines of this collaborative effort, the current status of contributed data, and the PDBe-KB infrastructure, which includes the data exchange format, the deposition system for added value annotations, the distributable database containing the assembled data, and programmatic access endpoints. We also describe a series of novel web-pages-the PDBe-KB aggregated views of structure data-which combine information on macromolecular structures from many PDB entries. We have recently released the first set of pages in this series, which provide an overview of available structural and functional information for a protein of interest, referenced by a UniProtKB accession

InterPro in 2019: improving coverage, classification and access to protein sequence annotations

The InterPro database (http://www.ebi.ac.uk/interpro/) classifies protein sequences into families and predicts the presence of functionally important domains and sites. Here, we report recent developments with InterPro (version 70.0) and its associated software, including an 18% growth in the size of the database in terms on new InterPro entries, updates to content, the inclusion of an additional entry type, refined modelling of discontinuous domains, and the development of a new programmatic interface and website. These developments extend and enrich the information provided by InterPro, and provide greater flexibility in terms of data access. We also show that InterPro's sequence coverage has kept pace with the growth of UniProtKB, and discuss how our evaluation of residue coverage may help guide future curation activities