PyBEL: a computational framework for Biological Expression Language

Gadiya

et al. 2020

Preprint

The SARS-CoV-2 outbreak was recently declared a worldwide pandemic. Infection triggers the respiratory tract disease COVID-19, which is accompanied by serious changes of clinical biomarkers such as hemoglobin and interleukins. The same parameters are altered during hemolysis, which is characterized by an increase in labile heme. We present two approaches that aim at analyzing a potential link between available heme and COVID-19 pathogenesis. Four COVID-19 related proteins, i.e. the host cell proteins ACE2 and TMPRSS2 as well as the viral protein 7a and S protein, were identified as potential heme binders. We also performed a detailed analysis of the common pathways induced by heme and SARS-CoV-2 by superimposition of knowledge graphs covering heme biology and COVID-19 pathophysiology. Herein, focus was laid on inflammatory pathways, and distinct biomarkers as the linking elements. Finally, the results substantially improve our understanding of COVID-19 infections and disease progression of patients with different clinical backgrounds and expand the diagnostic and treatment options.

Section: Modeling the Interplay Between Sars-cov-2 And Hemementioning

confidence: 99%

Unravelling the debate on heme effects in COVID-19 infections

Hopp

Gadiya

et al. 2020

Preprint

“…While the list of published BEL-specific algorithms is currently short (e.g., Reverse Causal Reasoning [32], Network Perturbation Amplitude [33], etc. ), recent developments in the BEL software ecosystem have improved the accessibility and utility of BEL and have motivated its wider adoption [34]. Unfortunately, unlike many of the other focuses of web applications, algorithms have remained confined to use by bioinformatics and inaccessible to a wider audience of researchers across disciplines.…”

Section: /18mentioning

confidence: 99%

“…The first point of entry for many users of BEL Commons will be through its BEL uploader, which allows users to choose a file from their computer to upload and to toggle common parsing and compilation parameters. After submitting, users' files are sent to an asynchronous task queue, implemented with RabbitMQ ( https://www.rabbitmq.com ) and Celery ( http://www.celeryproject.org ), that performs parsing, validation, and compilation with PyBEL [34] in the background. Errors and warnings encountered during parsing are enumerated, statistics over the resulting network are produced, biological network motifs are identified, and finally, the submitter is notified upon completion.…”

Section: Network Uploadermentioning

confidence: 99%

“…Above the explorer is the general tool box that includes several additional interactions for exploration, analysis, and export of the network using the serializers described by Hoyt, et al [34]. Notably, it contains a path mining tool that enables path searches between given nodes with fine-granular, configurable settings (e.g., directedness, path search algorithm, application of filters for pathologies, etc.).…”

Section: /18mentioning

confidence: 99%

See 1 more Smart Citation

BEL Commons: an environment for exploration and analysis of networks encoded in Biological Expression Language

Hoyt

Hofmann-Apitius

2018

Preprint

Self Cite

The rapid accumulation of knowledge in the field of systems and networks biology during recent years requires complex, but user-friendly and accessible web applications that allow from visualization to complex algorithmic analysis. While several web applications exist with various focuses on creation, revision, curation, storage, integration, collaboration, exploration, visualization, and analysis, many of these services remain disjoint and have yet to be packaged into a cohesive environment.Here, we present BEL Commons; an integrative knowledge discovery environment for networks encoded in the Biological Expression Language (BEL). Users can upload files in BEL to be parsed, validated, compiled, and stored with fine-granular permissions. After, users can summarize, explore, and optionally shared their networks with the scientific community. We have implemented a query builder wizard to help users find the relevant portions of increasingly large and complex networks and a visualization interface that allows them to explore their resulting networks. Finally, we have included a dedicated analytical service for performing data-driven analysis of knowledge networks to support hypothesis generation.This web application can be freely accessed at https://bel-commons.scai.fraunhofer.de .

“…Ultimately, the knowledge assembly comprised relations from 641 unique citations. Finally, the PyBEL framework [30] was used to parse and validate the syntax and semantics of the underlying BEL Script. A summary of the contents of the Epilepsy Knowledge…”

Section: Relation Extractionmentioning

confidence: 99%

A systematic approach for identifying shared mechanisms in epilepsy and its comorbidities

Hoyt

Balzer

et al. 2018

Preprint

Self Cite

Cross-sectional epidemiological studies have shown that the incidence of several nervous system diseases is more frequent in epilepsy patients than in the general population. Some comorbidities (e.g., Alzheimer's disease and Parkinson's disease) are also risk factors for the development of seizures; suggesting they may share pathophysiological mechanisms with epilepsy.A literature-based approach was used to identify gene overlap between epilepsy and its comorbidities as a proxy for a shared genetic basis for disease, or genetic pleiotropy, as a first effort to identify shared mechanisms. While the results identified neurological disorders as the group of diseases with the highest gene overlap, this analysis was insufficient for identifying putative common mechanisms shared across epilepsy and its comorbidities. This motivated the use of a dedicated literature mining and knowledge assembly approach in which a cause-and-effect model of epilepsy was captured with Biological Expression Language.After enriching the knowledge assembly with information surrounding epilepsy, its risk factors, its comorbidities, and antiepileptic drugs, a novel comparative mechanism enrichment approach was used to propose several downstream effectors (including the GABA receptor, GABAergic pathways, etc.) that could explain the therapeutic effects carbamazepine in both the contexts of epilepsy and AD.We have made the Epilepsy Knowledge Assembly available at