SABIO-RK: an updated resource for manually curated biochemical reaction kinetics

Wittig, Ulrike; Rey, Maja; Weidemann, Andreas; Kania, Renate; Müller, Wolfgang G.

doi:10.1093/nar/gkx1065

Cited by 136 publications

(118 citation statements)

References 30 publications

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“…This process is challenging because any given reaction depends on its cellular and physiological context, which makes it difficult to parameterise. Software support of tools like SBMLsqueezer [21] and reaction kinetics databases like SABIO-RK [310] are indispensable in this effort. Nevertheless, the most critical factor is the availability of experimentally validated parameters that can be reliably applied in SARS-CoV-2 modelling scenarios.…”

Section: Parallel Effortsmentioning

confidence: 99%

COVID-19 Disease Map, a computational knowledge repository of SARS-CoV-2 virus-host interaction mechanisms

Ostaszewski

Niarakis

Mazein

et al. 2020

Preprint

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We hereby describe a large-scale community effort to build an open-access, interoperable, and computable repository of COVID-19 molecular mechanisms - the COVID-19 Disease Map. We discuss the tools, platforms, and guidelines necessary for the distributed development of its contents by a multi-faceted community of biocurators, domain experts, bioinformaticians, and computational biologists. We highlight the role of relevant databases and text mining approaches in enrichment and validation of the curated mechanisms. We describe the contents of the map and their relevance to the molecular pathophysiology of COVID-19 and the analytical and computational modelling approaches that can be applied to the contents of the COVID-19 Disease Map for mechanistic data interpretation and predictions. We conclude by demonstrating concrete applications of our work through several use cases.

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Section: Parallel Effortsmentioning

confidence: 99%

COVID-19 Disease Map, a computational knowledge repository of SARS-CoV-2 virus-host interaction mechanisms

Ostaszewski

Niarakis

Mazein

et al. 2020

Preprint

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“…Because research often requires many types of data, Datanator includes several types of quantitative and categorical data. Currently, this includes 3,841 measurements of the concentrations of 1,621 metabolites aggregated from ECMDB, 9 YMDB, 10 and several articles; 589 reconstructed RNA modification profiles aggregated from MODOMICS; 11 75,836 measured RNA half-lives aggregated from several articles; 2,634,941 measurements of the abundance of 846,970 proteins aggregated from PaxDB; 12 4,083 reconstructed protein modification profiles aggregated from PRO; 13 and 61,734 measurements of the rate parameters of 37,858 reactions aggregated from SABIO-RK 14 (Figure 1a). In addition, we are working to include nearly 1,000,000 measurements of RNA localizations from RNALocate, 15 lncATLAS, 16 and one article; over 100,000 measured and predicted protein localizations from eSLDB, 17 the Human Protein Atlas, 18 PSORTdb, 19 and Sub-Cell; 20 more than 50,000 measurements of protein half-lives from nine publications; more than 200,000 additional measurements of reaction parameters from BRENDA; 21 and reaction flux measurements for 36 organisms from CeCaFDB.…”

Section: Integrated Database Of Molecular Datamentioning

confidence: 99%

Datanator: an integrated database of molecular data for quantitatively modeling cellular behavior

Roth

Lian

Pochiraju

et al. 2020

Preprint

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Integrative research about multiple biochemical subsystems has significant potential to help advance biology, bioengineering, and medicine. However, it is difficult to obtain the diverse data needed for integrative research. To facilitate biochemical research, we developed Datanator (https://datanator.info), an integrated database and set of tools for finding clouds of multiple types of molecular data about specific molecules and reactions in specific organisms and environments, as well as data about chemically-similar molecules and reactions in phylogenetically-similar organisms in similar environments. Currently, Datanator includes metabolite concentrations, RNA modifications and half-lives, protein abundances and modifications, and reaction rate constants about a broad range of organisms. Going forward, we aim to launch a community initiative to curate additional data. Datanator also provides tools for filtering, visualizing, and exporting these data clouds. We believe that Datanator can facilitate a wide range of research from integrative mechanistic models, such as whole-cell models, to comparative data-driven analyses of multiple organisms.

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“…Datasets are available in the literature and in established databases, such as BRENDA [56] and SABIO-RK [57]. However, most literature-based datasets are unstructured and difficult to assess.…”

Section: Parameterization or Executable Mathematical Modelsmentioning

confidence: 99%

Community-driven roadmap for integrated disease maps

Ostaszewski¹,

Gebel²,

Kuperstein³

et al. 2018

Preprint

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The Disease Maps Project builds upon a network of scientific and clinical groups that exchange best practices, share information, and develop systems biomedicine tools. The project aims for an integrated, highly curated and user-friendly platform for disease-related knowledge. The primary focus of disease maps is on interconnected signaling, metabolic and gene regulatory network pathways represented in standard formats. The involvement of domain experts ensures that the key disease hallmarks are covered and relevant, up-to-date knowledge is adequately represented. Expert-curated and computer readable, disease maps may serve as a compendium of knowledge, allow for data-supported hypothesis generation, or serve as a scaffold for the generation of predictive mathematical models.This article summarizes the 2nd Disease Maps Community meeting, highlighting its important topics and outcomes. We outline milestones on the roadmap for the future development of disease maps, including creating and maintaining standardized disease maps; sharing parts of maps that encode common human disease mechanisms; providing technical solutions for complexity management of maps; and web-tools for in-depth exploration of such maps. A dedicated discussion was focused on mathematical modeling approaches, as one of the main goals of disease map development is the generation of mathematically interpretable representations in order to predict disease comorbidity or drug response and to suggest drug repositioning, altogether supporting clinical decisions.

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SABIO-RK: an updated resource for manually curated biochemical reaction kinetics

Cited by 136 publications

References 30 publications

COVID-19 Disease Map, a computational knowledge repository of SARS-CoV-2 virus-host interaction mechanisms

COVID-19 Disease Map, a computational knowledge repository of SARS-CoV-2 virus-host interaction mechanisms

Datanator: an integrated database of molecular data for quantitatively modeling cellular behavior

Community-driven roadmap for integrated disease maps

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