118,347 research outputs found
SIGNOR: a database of causal relationships between biological entities
No full textAssembly of large biochemical networks can be achieved by confronting new cell-specific experimental data with an interaction subspace constrained by prior literature evidence. The SIGnaling Network Open Resource, SIGNOR (available on line at http://signor.uniroma2.it), was developed to support such a strategy by providing a scaffold of prior experimental evidence of causal relationships between biological entities. The core of SIGNOR is a collection of approximately 12 000 manually-annotated causal relationships between over 2800 human proteins participating in signal transduction. Other entities annotated in SIGNOR are complexes, chemicals, phenotypes and stimuli. The information captured in SIGNOR can be represented as a signed directed graph illustrating the activation/inactivation relationships between signalling entities. Each entry is associated to the post-translational modifications that cause the activation/inactivation of the target proteins. More than 4900 modified residues causing a change in protein concentration or activity have been curated and linked to the modifying enzymes (about 351 human kinases and 94 phosphatases). Additional modifications such as ubiquitinations, sumoylations, acetylations and their effect on the modified target proteins are also annotated. This wealth of structured information can support experimental approaches based on multi-parametric analysis of cell systems after physiological or pathological perturbations and to assemble large logic models
SIGNOR 2.0, the SIGnaling Network Open Resource 2.0: 2019 update
No full textThe SIGnaling Network Open Resource 2.0 (SIGNOR 2.0) is a public repository that stores signaling information as binary causal relationships between biological entities. The captured information is represented graphically as a signed directed graph. Each signaling relationship is associated to an effect (up/down-regulation) and to the mechanism (e.g. binding, phosphorylation, transcriptional activation, etc.) causing the up/down-regulation of the target entity. Since its first release, SIGNOR has undergone a significant content increase and the number of annotated causal interactions have almost doubled. SIGNOR 2.0 now stores almost 23 000 manually-annotated causal relationships between proteins and other biologically relevant entities: chemicals, phenotypes, complexes, etc. We describe here significant changes in curation policy and a new confidence score, which is assigned to each interaction. We have also improved the compliance to the FAIR data principles by providing (i) SIGNOR stable identifiers, (ii) programmatic access through REST APIs, (iii) bioschemas and (iv) downloadable data in standard-compliant formats, such as PSI-MI CausalTAB and GMT. The data are freely accessible and downloadable at https://signor.uniroma2.it/
SIGNORApp: a Cytoscape 3 application to access SIGNOR data
No full textSummary: SIGNORApp is a Cytoscape 3 (3.8 and later) application that provides access to causal interactions annotated in the SIGNOR resource. The application builds networks that can be represented as weighted, signed, directed graphs, where nodes are interacting biological entities and edges represent causal interactions captured by expert curators from experiments reported in peer reviewed journals. Users can query the SIGNOR dataset with i) single or multiple entity name(s) or identifier(s) and optionally they may require to include in the output network their interacting partners; ii) browse pathways that are annotated in the SIGNOR resource; iii) extract the entire causal interactome. The app offers two visualizations modes: one only displaying entity interactions and a second emphasizing the post translational modifications occurring as a consequence of the interaction. In addition, users can click on nodes and edges to access entity and interaction annotations. Causal information is available for three model organisms: H. sapiens, M. musculus and R. norvegicus.
Availability: SIGNORApp has been developed for Cytoscape 3 (3.8 and later) in the Java programming language. The latest source code and the plugin can be found at: https://github.com/SIGNORcysAPP/signor-app and https://apps.cytoscape.org/apps/signorapp, respectively
SIGNOR 2.0, the SIGnaling Network Open Resource 2.0: 2019 update
No full textThe SIGnaling Network Open Resource 2.0 (SIGNOR 2.0) is a public repository that stores signaling information as binary causal relationships between biological entities. The captured information is represented graphically as a signed directed graph. Each signaling relationship is associated to an effect (up/down-regulation) and to the mechanism (e.g. binding, phosphorylation, transcriptional activation, etc.) causing the up/down-regulation of the target entity. Since its first release, SIGNOR has undergone a significant content increase and the number of annotated causal interactions have almost doubled. SIGNOR 2.0 now stores almost 23 000 manually-annotated causal relationships between proteins and other biologically relevant entities: chemicals, phenotypes, complexes, etc. We describe here significant changes in curation policy and a new confidence score, which is assigned to each interaction. We have also improved the compliance to the FAIR data principles by providing (i) SIGNOR stable identifiers, (ii) programmatic access through REST APIs, (iii) bioschemas and (iv) downloadable data in standard-compliant formats, such as PSI-MI CausalTAB and GMT. The data are freely accessible and downloadable at https://signor.uniroma2.it/
Ascorbate oxidation catalyzed by Bis(histidine)copper(II)
No full textThe kinetics of ascorbic acid oxidation by molecular oxygen, catalyzed by bis(histidine)copper(II) (CuL22+), was followed in 0.1 M phosphate buffer at pH 7.0. Saturation of the oxidation rate was observed at increasing O2, ascorbate and CuL22+ concentrations. The oxidation state of the copper ion during the catalysis and the concentration of the ascorbyl radical were followed by ESR and/or by optical spectroscopy. No significant reduction of Cu(II) was observed under vacuum or in the presence of oxygen at ascorbate concentrations <20 mM. Evidence for the binding of ascorbate to CuL22+ was found by ESR, and a stability constant of 20 M-1 was estimated. We suggested a mechanism which is consistent with our experimental findings and explains some of the contradictory data reported in the past by various authors. The saturation of the reaction rate on increasing [CuL22+] is explained in terms of its catalytic effect on ascorbate oxidation and the superoxide dismutase-like activity of this complex. The experimental concentration of the ascorbyl radical, which is an intermediate product, was in good agreement with that calculated on the basis of the proposed mechanism
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
SIGNOR: a new signaling network open resource
No full textStandardization and analysis of large datasets have played, in recent decades, a key role in many fields of knowledge including biology. Biological information, starting from the sequence of a protein to its function, are increasingly being analyzed and made accessible to the scientific community through the use of web-services and databases. In particular the protein-protein interaction network has proved a crucial resource to promote the advancement of systems biology and facilitate the understanding of events occurring in biological systems. Despite the many insights we gained from the analysis of this information, currently available interactomes have several shortcomings. One of the most important limitations is the lack of information on protein regulation and on the direction of the information flow that from the sense of a stimulus leads to the cellular response. In addition, in the available picture, information about the participation of other important biological entities (e.g., small molecule, transcription factors and genes) is still missing. To this purpose, in recent years, different signalling resources have been created, with the aim of capturing all the signal transduction information reported in the scientific literature, organizing it in a structured format and offering it to the community in a user friendly way. Our group decided to create a new resource to "fill the gap" between protein-protein interactions and signalling networks and at the same time, to provide researchers with a tool to support experimental approaches based on multi-parametric analysis of cell systems. SIGNOR (http://signor.uniroma2.it), the Signalling Network Open Resource is a new database-centered application specifically designed to facilitate the storage and analysis of directed molecular interaction and regulation. An ongoing curation effort aims at making SIGNOR a prominent resource in the biological community by offering a comprehensive network of experimentally validated functional relationships between signalling proteins that can be used as an a priori model for optimization strategies. At the time of writing, the core of SIGNOR is a collection of approximately 7400 manually-annotated logic relationships between proteins and other biological entities that participate in signal transduction. Each relationship is linked to the literature reporting the experimental evidence and is assigned a score. These numbers are expected to increase thanks to the manual annotation of further publications carried out by our expert curators. Scientists from various branches of biology may find SIGNOR a precious resource to foster their own research
Effetto dell'emolisi sulla quantificazione delle principali emoproteine del suino
No full textSwine erythrocyte fragility is likely to produce a
variable degree of haemolysis during blood sampling and free haemoglobin may unexpectedly affect the analytes quantification.
The aim of this work was to determine the cut-off hresholds to consider some seroproteins as acceptable. To this end, we induced steady levels of physical haemolysis in 3 aliquots from 30 unhaemolytic sera and evaluated its effect on analytes quantification. To determine haemolysis level we compared a visual estimation (score 0 to 3) to haemolysis index (analytical), with optimal correlation at level 0-1-2
SIGNOR 3.0, the SIGnaling network open resource 3.0: 2022 update
No full textThe SIGnaling Network Open Resource (SIGNOR 3.0, ) is a public repository that captures causal information and represents it according to an 'activity-flow' model. SIGNOR provides freely-accessible static maps of causal interactions that can be tailored, pruned and refined to build dynamic and predictive models. Each signaling relationship is annotated with an effect (up/down-regulation) and with the mechanism (e.g. binding, phosphorylation, transcriptional activation, etc.) causing the regulation of the target entity. Since its latest release, SIGNOR has undergone a significant upgrade including: (i) a new website that offers an improved user experience and novel advanced search and graph tools; (ii) a significant content growth adding up to a total of approx. 33,000 manually-annotated causal relationships between more than 8900 biological entities; (iii) an increase in the number of manually annotated pathways, currently including pathways deregulated by SARS-CoV-2 infection or involved in neurodevelopment synaptic transmission and metabolism, among others; (iv) additional features such as new model to represent metabolic reactions and a new confidence score assigned to each interaction
Love sketch [music].
No full textCatalogue record generated as part of a batch load; "The following elegant canzonette, kindly dedicated by Signor L. Gorgioni to his friend Mr. R. Cocks …".; Also available online http://nla.gov.au/nla.mus-vn5715944
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