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Article ; Online: On the role of bacterial metalloproteases in COVID-19 associated cytokine storm.

Földvári-Nagy, László / Schnabel, Tamás / Dörnyei, Gabriella / Korcsmáros, Tamás / Lenti, Katalin

2021 Volume 19, Issue 1, Page(s) 7

Abstract: The cytokine release syndrome or cytokine storm, which is the hyper-induction of inflammatory responses has a central role in the mortality rate of COVID-19 and some other viral infections. Interleukin-6 (IL-6) is a key player in the development of ... ...

Abstract	The cytokine release syndrome or cytokine storm, which is the hyper-induction of inflammatory responses has a central role in the mortality rate of COVID-19 and some other viral infections. Interleukin-6 (IL-6) is a key player in the development of cytokine storms. Shedding of interleukin-6 receptor (IL-6Rα) results in the accumulation of soluble interleukin-6 receptors (sIL-6R). Only relatively few cells express membrane-bound IL-6Rα. However, sIL-6R can act on potentially all cells and organs through the ubiquitously expressed gp130, the coreceptor of IL-6Rα. Through this, so-called trans-signaling, IL-6-sIL-6R is a powerful factor in the development of cytokine storms and multiorgan involvement. Some bacteria (e.g., Serratia marcescens, Staphylococcus aureus, Pseudomonas aeruginosa, Listeria monocytogenes), commonly considered to cause co-infections during viral pneumonia, can directly induce the shedding of membrane receptors, including IL-6Rα, or enhance endogenous shedding mechanisms causing the increase of sIL-6R level. Here we hypothesise that bacteria promoting shedding and increase the sIL-6R level can be an important contributing factor for the development of cytokine storms. Therefore, inhibition of IL-6Rα shedding by drastically reducing the number of relevant bacteria may be a critical element in reducing the chance of a cytokine storm. Validation of this hypothesis can support the consideration of the prophylactic use of antibiotics more widely and at an earlier stage of infection to decrease the mortality rate of COVID-19. Video abstract.
MeSH term(s)	Bacteria/enzymology ; Bacterial Proteins/metabolism ; COVID-19/complications ; COVID-19/pathology ; COVID-19/virology ; Cytokine Release Syndrome/etiology ; Cytokine Release Syndrome/microbiology ; Humans ; Interleukin-6/metabolism ; Metalloproteases/metabolism ; Receptors, Interleukin-6/metabolism ; SARS-CoV-2/isolation & purification ; Signal Transduction
Chemical Substances	Bacterial Proteins ; Interleukin-6 ; Receptors, Interleukin-6 ; Metalloproteases (EC 3.4.-)
Language	English
Publishing date	2021-01-13
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2126315-2
ISSN	1478-811X ; 1478-811X
ISSN (online)	1478-811X
ISSN	1478-811X
DOI	10.1186/s12964-020-00699-3
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Article ; Online: Probiotic supplementation during antibiotic treatment is unjustified in maintaining the gut microbiome diversity: a systematic review and meta-analysis.

Éliás, Anna Júlia / Barna, Viktória / Patoni, Cristina / Demeter, Dóra / Veres, Dániel Sándor / Bunduc, Stefania / Erőss, Bálint / Hegyi, Péter / Földvári-Nagy, László / Lenti, Katalin

BMC medicine

2023 Volume 21, Issue 1, Page(s) 262

Abstract: Background: Probiotics are often used to prevent antibiotic-induced low-diversity dysbiosis, however their effect is not yet sufficiently summarized in this regard. We aimed to investigate the effects of concurrent probiotic supplementation on gut ... ...

Abstract	Background: Probiotics are often used to prevent antibiotic-induced low-diversity dysbiosis, however their effect is not yet sufficiently summarized in this regard. We aimed to investigate the effects of concurrent probiotic supplementation on gut microbiome composition during antibiotic therapy. Methods: We performed a systematic review and meta-analysis of randomized controlled trials reporting the differences in gut microbiome diversity between patients on antibiotic therapy with and without concomitant probiotic supplementation. The systematic search was performed in three databases (MEDLINE (via PubMed), Embase, and Cochrane Central Register of Controlled Trials (CENTRAL)) without filters on 15 October 2021. A random-effects model was used to estimate pooled mean differences (MD) with 95% confidence intervals (CI). This review was registered on PROSPERO (CRD42021282983). Results: Of 11,769 identified articles, 15 were eligible in the systematic review and 5 in the meta-analyses. Quantitative data synthesis for Shannon (MD = 0.23, 95% CI: [(-)0.06-0.51]), Chao1 (MD = 11.59 [(-)18.42-41.60]) and observed OTUs (operational taxonomic unit) (MD = 17.15 [(-)9.43-43.73]) diversity indices revealed no significant difference between probiotic supplemented and control groups. Lacking data prevented meta-analyzing other diversity indices; however, most of the included studies reported no difference in the other reported α- and ß-diversity indices between the groups. Changes in the taxonomic composition varied across the eligible studies but tended to be similar in both groups. However, they showed a potential tendency to restore baseline levels in both groups after 3-8 weeks. This is the first meta-analysis and the most comprehensive review of the topic to date using high quality methods. The limited number of studies and low sample sizes are the main limitations of our study. Moreover, there was high variability across the studies regarding the indication of antibiotic therapy and the type, dose, and duration of antimicrobials and probiotics. Conclusions: Our results showed that probiotic supplementation during antibiotic therapy was not found to be influential on gut microbiome diversity indices. Defining appropriate microbiome diversity indices, their standard ranges, and their clinical relevance would be crucial.
MeSH term(s)	Humans ; Gastrointestinal Microbiome ; Probiotics/therapeutic use ; Probiotics/adverse effects ; Dietary Supplements ; Anti-Bacterial Agents/adverse effects ; Dysbiosis
Chemical Substances	Anti-Bacterial Agents
Language	English
Publishing date	2023-07-19
Publishing country	England
Document type	Meta-Analysis ; Systematic Review ; Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2131669-7
ISSN	1741-7015 ; 1741-7015
ISSN (online)	1741-7015
ISSN	1741-7015
DOI	10.1186/s12916-023-02961-0
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Article ; Online: A De Quervain-féle tendinopathia kezelése konzervatív módszerekkel.

Földvári-Nagy, László / Takács, Johanna / Hetthéssy, Judit Réka / Mayer, Ágnes Andrea / Szakács, Noémi / Szávin-Pósa, Ágnes / Lenti, Katalin

Orvosi hetilap

2020 Volume 161, Issue 11, Page(s) 419–424

Abstract: Introduction: ...

Title translation	Treatment of De Quervain's tendinopathy with conservative methods.
Abstract	Introduction:
MeSH term(s)	Conservative Treatment ; De Quervain Disease/diagnosis ; De Quervain Disease/therapy ; Humans ; Pain ; Pain Measurement ; Physical Therapy Modalities ; Tendinopathy/diagnosis ; Tendinopathy/therapy ; Treatment Outcome
Language	Hungarian
Publishing date	2020-02-21
Publishing country	Hungary
Document type	Journal Article
ZDB-ID	123879-6
ISSN	1788-6120 ; 0030-6002
ISSN (online)	1788-6120
ISSN	0030-6002
DOI	10.1556/650.2020.31672
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Article ; Online: AutophagyNet: high-resolution data source for the analysis of autophagy and its regulation.

Autophagy

2023 Volume 20, Issue 1, Page(s) 188–201

Abstract: Macroautophagy/autophagy is a highly-conserved catabolic procss eliminating dysfunctional cellular components and invading pathogens. Autophagy malfunction contributes to disorders such as cancer, neurodegenerative and inflammatory diseases. ... ...

Abstract	Macroautophagy/autophagy is a highly-conserved catabolic procss eliminating dysfunctional cellular components and invading pathogens. Autophagy malfunction contributes to disorders such as cancer, neurodegenerative and inflammatory diseases. Understanding autophagy regulation in health and disease has been the focus of the last decades. We previously provided an integrated database for autophagy research, the Autophagy Regulatory Network (ARN). For the last eight years, this resource has been used by thousands of users. Here, we present a new and upgraded resource, AutophagyNet. It builds on the previous database but contains major improvements to address user feedback and novel needs due to the advancement in omics data availability. AutophagyNet contains updated interaction curation and integration of over 280,000 experimentally verified interactions between core autophagy proteins and their protein, transcriptional and post-transcriptional regulators as well as their potential upstream pathway connections. AutophagyNet provides annotations for each core protein about their role: 1) in different types of autophagy (mitophagy, xenophagy, etc.); 2) in distinct stages of autophagy (initiation, expansion, termination, etc.); 3) with subcellular and tissue-specific localization. These annotations can be used to filter the dataset, providing customizable download options tailored to the user's needs. The resource is available in various file formats (e.g. CSV, BioPAX and PSI-MI), and data can be analyzed and visualized directly in Cytoscape. The multi-layered regulation of autophagy can be analyzed by combining AutophagyNet with tissue- or cell type-specific (multi-)omics datasets (e.g. transcriptomic or proteomic data). The resource is publicly accessible at http://autophagynet.org.
MeSH term(s)	Autophagy/physiology ; Proteomics ; Beclin-1 ; Mitophagy ; Signal Transduction/genetics ; MicroRNAs
Chemical Substances	Beclin-1 ; MicroRNAs
Language	English
Publishing date	2023-08-17
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2454135-7
ISSN	1554-8635 ; 1554-8627
ISSN (online)	1554-8635
ISSN	1554-8627
DOI	10.1080/15548627.2023.2247737
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Article ; Online: Identification of critical paralog groups with indispensable roles in the regulation of signaling flow.

Modos, Dezso / Brooks, Johanne / Fazekas, David / Ari, Eszter / Vellai, Tibor / Csermely, Peter / Korcsmaros, Tamas / Lenti, Katalin

Scientific reports

2016 Volume 6, Page(s) 38588

Abstract: Extensive cross-talk between signaling pathways is required to integrate the myriad of extracellular signal combinations at the cellular level. Gene duplication events may lead to the emergence of novel functions, leaving groups of similar genes - termed ...

Abstract	Extensive cross-talk between signaling pathways is required to integrate the myriad of extracellular signal combinations at the cellular level. Gene duplication events may lead to the emergence of novel functions, leaving groups of similar genes - termed paralogs - in the genome. To distinguish critical paralog groups (CPGs) from other paralogs in human signaling networks, we developed a signaling network-based method using cross-talk annotation and tissue-specific signaling flow analysis. 75 CPGs were found with higher degree, betweenness centrality, closeness, and 'bowtieness' when compared to other paralogs or other proteins in the signaling network. CPGs had higher diversity in all these measures, with more varied biological functions and more specific post-transcriptional regulation than non-critical paralog groups (non-CPG). Using TGF-beta, Notch and MAPK pathways as examples, SMAD2/3, NOTCH1/2/3 and MEK3/6-p38 CPGs were found to regulate the signaling flow of their respective pathways. Additionally, CPGs showed a higher mutation rate in both inherited diseases and cancer, and were enriched in drug targets. In conclusion, the results revealed two distinct types of paralog groups in the signaling network: CPGs and non-CPGs. Thus highlighting the importance of CPGs as compared to non-CPGs in drug discovery and disease pathogenesis.
MeSH term(s)	Computational Biology/methods ; Databases, Genetic ; Humans ; Organ Specificity ; Signal Transduction/drug effects ; Workflow
Language	English
Publishing date	2016-12-06
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/srep38588
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Article ; Online: Adaptation and learning of molecular networks as a description of cancer development at the systems-level: potential use in anti-cancer therapies.

Gyurkó, Dávid M / Veres, Dániel V / Módos, Dezső / Lenti, Katalin / Korcsmáros, Tamás / Csermely, Peter

Seminars in cancer biology

2013 Volume 23, Issue 4, Page(s) 262–269

Abstract: There is a widening recognition that cancer cells are products of complex developmental processes. Carcinogenesis and metastasis formation are increasingly described as systems-level, network phenomena. Here we propose that malignant transformation is a ... ...

Abstract	There is a widening recognition that cancer cells are products of complex developmental processes. Carcinogenesis and metastasis formation are increasingly described as systems-level, network phenomena. Here we propose that malignant transformation is a two-phase process, where an initial increase of system plasticity is followed by a decrease of plasticity at late stages of carcinogenesis as a model of cellular learning. We describe the hallmarks of increased system plasticity of early, tumor initiating cells, such as increased noise, entropy, conformational and phenotypic plasticity, physical deformability, cell heterogeneity and network rearrangements. Finally, we argue that the large structural changes of molecular networks during cancer development necessitate a rather different targeting strategy in early and late phase of carcinogenesis. Plastic networks of early phase cancer development need a central hit, while rigid networks of late stage primary tumors or established metastases should be attacked by the network influence strategy, such as by edgetic, multi-target, or allo-network drugs. Cancer stem cells need special diagnosis and targeting, since their dormant and rapidly proliferating forms may have more rigid, or more plastic networks, respectively. The extremely high ability of cancer stem cells to change the rigidity/plasticity of their networks may be their key hallmark. The application of early stage-optimized anti-cancer drugs to late-stage patients may be a reason of many failures in anti-cancer therapies. Our hypotheses presented here underlie the need for patient-specific multi-target therapies applying the correct ratio of central hits and network influences - in an optimized sequence.
MeSH term(s)	Antineoplastic Agents/therapeutic use ; Cell Transformation, Neoplastic/drug effects ; Cell Transformation, Neoplastic/metabolism ; Cell Transformation, Neoplastic/pathology ; Humans ; Metabolic Networks and Pathways/drug effects ; Models, Biological ; Neoplasms/drug therapy ; Neoplasms/metabolism ; Neoplasms/pathology ; Neoplastic Stem Cells/drug effects ; Neoplastic Stem Cells/metabolism ; Neoplastic Stem Cells/pathology ; Signal Transduction
Chemical Substances	Antineoplastic Agents
Language	English
Publishing date	2013-08
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Review
ZDB-ID	1033980-2
ISSN	1096-3650 ; 1044-579X
ISSN (online)	1096-3650
ISSN	1044-579X
DOI	10.1016/j.semcancer.2013.06.005
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Article ; Online: Targets of drugs are generally, and targets of drugs having side effects are specifically good spreaders of human interactome perturbations.

Perez-Lopez, Áron R / Szalay, Kristóf Z / Türei, Dénes / Módos, Dezső / Lenti, Katalin / Korcsmáros, Tamás / Csermely, Peter

Scientific reports

2015 Volume 5, Page(s) 10182

Abstract: Network-based methods are playing an increasingly important role in drug design. Our main question in this paper was whether the efficiency of drug target proteins to spread perturbations in the human interactome is larger if the binding drugs have side ... ...

Abstract	Network-based methods are playing an increasingly important role in drug design. Our main question in this paper was whether the efficiency of drug target proteins to spread perturbations in the human interactome is larger if the binding drugs have side effects, as compared to those which have no reported side effects. Our results showed that in general, drug targets were better spreaders of perturbations than non-target proteins, and in particular, targets of drugs with side effects were also better spreaders of perturbations than targets of drugs having no reported side effects in human protein-protein interaction networks. Colorectal cancer-related proteins were good spreaders and had a high centrality, while type 2 diabetes-related proteins showed an average spreading efficiency and had an average centrality in the human interactome. Moreover, the interactome-distance between drug targets and disease-related proteins was higher in diabetes than in colorectal cancer. Our results may help a better understanding of the network position and dynamics of drug targets and disease-related proteins, and may contribute to develop additional, network-based tests to increase the potential safety of drug candidates.
MeSH term(s)	Colorectal Neoplasms/metabolism ; Diabetes Mellitus, Type 2/metabolism ; Drug Delivery Systems ; Drug-Related Side Effects and Adverse Reactions/metabolism ; Humans ; Neoplasm Proteins/metabolism ; Protein Interaction Maps ; Time Factors
Chemical Substances	Neoplasm Proteins
Language	English
Publishing date	2015-05-11
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/srep10182
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Article: Neighbours of cancer-related proteins have key influence on pathogenesis and could increase the drug target space for anticancer therapies.

Módos, Dezső / Bulusu, Krishna C / Fazekas, Dávid / Kubisch, János / Brooks, Johanne / Marczell, István / Szabó, Péter M / Vellai, Tibor / Csermely, Péter / Lenti, Katalin / Bender, Andreas / Korcsmáros, Tamás

NPJ systems biology and applications

2017 Volume 3, Page(s) 2

Abstract: Even targeted chemotherapies against solid cancers show a moderate success increasing the need to novel targeting strategies. To address this problem, we designed a systems-level approach investigating the neighbourhood of mutated or differentially ... ...

Abstract	Even targeted chemotherapies against solid cancers show a moderate success increasing the need to novel targeting strategies. To address this problem, we designed a systems-level approach investigating the neighbourhood of mutated or differentially expressed cancer-related proteins in four major solid cancers (colon, breast, liver and lung). Using signalling and protein-protein interaction network resources integrated with mutational and expression datasets, we analysed the properties of the direct and indirect interactors (first and second neighbours) of cancer-related proteins, not found previously related to the given cancer type. We found that first neighbours have at least as high degree, betweenness centrality and clustering coefficient as cancer-related proteins themselves, indicating a previously unknown central network position. We identified a complementary strategy for mutated and differentially expressed proteins, where the affect of differentially expressed proteins having smaller network centrality is compensated with high centrality first neighbours. These first neighbours can be considered as key, so far hidden, components in cancer rewiring, with similar importance as mutated proteins. These observations strikingly suggest targeting first neighbours as a novel strategy for disrupting cancer-specific networks. Remarkably, our survey revealed 223 marketed drugs already targeting first neighbour proteins but applied mostly outside oncology, providing a potential list for drug repurposing against solid cancers. For the very central first neighbours, whose direct targeting would cause several side effects, we suggest a cancer-mimicking strategy by targeting their interactors (second neighbours of cancer-related proteins, having a central protein affecting position, similarly to the cancer-related proteins). Hence, we propose to include first neighbours to network medicine based approaches for (but not limited to) anticancer therapies.
Language	English
Publishing date	2017-05-26
Publishing country	England
Document type	Journal Article
ISSN	2056-7189
ISSN	2056-7189
DOI	10.1038/s41540-017-0003-6
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Article ; Online: NRF2-ome: an integrated web resource to discover protein interaction and regulatory networks of NRF2.

Türei, Dénes / Papp, Diána / Fazekas, Dávid / Földvári-Nagy, László / Módos, Dezső / Lenti, Katalin / Csermely, Péter / Korcsmáros, Tamás

Oxidative medicine and cellular longevity

2013 Volume 2013, Page(s) 737591

Abstract: NRF2 is the master transcriptional regulator of oxidative and xenobiotic stress responses. NRF2 has important roles in carcinogenesis, inflammation, and neurodegenerative diseases. We developed an online resource, NRF2-ome, to provide an integrated and ... ...

Abstract	NRF2 is the master transcriptional regulator of oxidative and xenobiotic stress responses. NRF2 has important roles in carcinogenesis, inflammation, and neurodegenerative diseases. We developed an online resource, NRF2-ome, to provide an integrated and systems-level database for NRF2. The database contains manually curated and predicted interactions of NRF2 as well as data from external interaction databases. We integrated NRF2 interactome with NRF2 target genes, NRF2 regulating TFs, and miRNAs. We connected NRF2-ome to signaling pathways to allow mapping upstream NRF2 regulatory components that could directly or indirectly influence NRF2 activity totaling 35,967 protein-protein and signaling interactions. The user-friendly website allows researchers without computational background to search, browse, and download the database. The database can be downloaded in SQL, CSV, BioPAX, SBML, PSI-MI, and in a Cytoscape CYS file formats. We illustrated the applicability of the website by suggesting a posttranscriptional negative feedback of NRF2 by MAFG protein and raised the possibility of a connection between NRF2 and the JAK/STAT pathway through STAT1 and STAT3. NRF2-ome can also be used as an evaluation tool to help researchers and drug developers to understand the hidden regulatory mechanisms in the complex network of NRF2.
MeSH term(s)	Databases, Protein ; Gene Regulatory Networks ; Humans ; Internet ; NF-E2-Related Factor 2/metabolism ; Protein Interaction Maps ; Workflow
Chemical Substances	NF-E2-Related Factor 2
Language	English
Publishing date	2013-04-17
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2455981-7
ISSN	1942-0994 ; 1942-0994
ISSN (online)	1942-0994
ISSN	1942-0994
DOI	10.1155/2013/737591
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Article ; Online: SignaLink3: a multi-layered resource to uncover tissue-specific signaling networks.

Csabai, Luca / Fazekas, Dávid / Kadlecsik, Tamás / Szalay-Bekő, Máté / Bohár, Balázs / Madgwick, Matthew / Módos, Dezső / Ölbei, Márton / Gul, Lejla / Sudhakar, Padhmanand / Kubisch, János / Oyeyemi, Oyebode James / Liska, Orsolya / Ari, Eszter / Hotzi, Bernadette / Billes, Viktor A / Molnár, Eszter / Földvári-Nagy, László / Csályi, Kitti /

Demeter, Amanda / Pápai, Nóra / Koltai, Mihály / Varga, Máté / Lenti, Katalin / Farkas, Illés J / Türei, Dénes / Csermely, Péter / Vellai, Tibor / Korcsmáros, Tamás

Nucleic acids research

2021 Volume 50, Issue D1, Page(s) D701–D709

Abstract: Signaling networks represent the molecular mechanisms controlling a cell's response to various internal or external stimuli. Most currently available signaling databases contain only a part of the complex network of intertwining pathways, leaving out key ...

Abstract	Signaling networks represent the molecular mechanisms controlling a cell's response to various internal or external stimuli. Most currently available signaling databases contain only a part of the complex network of intertwining pathways, leaving out key interactions or processes. Hence, we have developed SignaLink3 (http://signalink.org/), a value-added knowledge-base that provides manually curated data on signaling pathways and integrated data from several types of databases (interaction, regulation, localisation, disease, etc.) for humans, and three major animal model organisms. SignaLink3 contains over 400 000 newly added human protein-protein interactions resulting in a total of 700 000 interactions for Homo sapiens, making it one of the largest integrated signaling network resources. Next to H. sapiens, SignaLink3 is the only current signaling network resource to provide regulatory information for the model species Caenorhabditis elegans and Danio rerio, and the largest resource for Drosophila melanogaster. Compared to previous versions, we have integrated gene expression data as well as subcellular localization of the interactors, therefore uniquely allowing tissue-, or compartment-specific pathway interaction analysis to create more accurate models. Data is freely available for download in widely used formats, including CSV, PSI-MI TAB or SQL.
MeSH term(s)	Animals ; Caenorhabditis elegans/genetics ; Databases, Genetic ; Drosophila melanogaster/genetics ; Gene Regulatory Networks/genetics ; Humans ; Protein Interaction Maps/genetics ; Signal Transduction/genetics ; Zebrafish/genetics
Language	English
Publishing date	2021-10-11
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	186809-3
ISSN	1362-4962 ; 1362-4954 ; 0301-5610 ; 0305-1048
ISSN (online)	1362-4962 ; 1362-4954
ISSN	0301-5610 ; 0305-1048
DOI	10.1093/nar/gkab909
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