sbv IMPROVER: Modern Approach to Systems Biology

Abstract

The increasing amount and variety of data in biosciences call for innovative methods of visualization, scientific verification, and pathway analysis. Novel approaches to biological networks and research quality control are important because of their role in development of new products, improvement, and acceleration of existing health policies and research for novel ways of solving scientific challenges. One such approach is sbv IMPROVER. It is a platform that uses crowdsourcing and verification to create biological networks with easy public access. It contains 120 networks built in Biological Expression Language (BEL) to interpret data from PubMed articles with high-quality verification available for free on the CBN database. Computable, human-readable biological networks with a structured syntax are a powerful way of representing biological information generated from high-density data. This article presents sbv IMPROVER, a crowd-verification approach for the visualization and expansion of biological networks.

Re-curation and rational enrichment of knowledge graphs in Biological Expression Language

“…but explicitly exclude the biological mechanisms through which the inhibitors' targets result in Tau aggregation that would better be curated during a different project focusing on capturing molecular biology from its primary literature. While there is no alternative to proper planning, several semi-automated curation workflows such as BEL information extraction workflow (BELIEF) (34) and the sbv IMPROVER (35) provide assistance by automatically detecting entities and relations for curators to accept or fix in order to increase productivity and enforce correct syntax and semantics. However, these and similar systems are limited in their ability to capture the relevant chemistry and biology, and reversion to manual curation is often necessary.…”

High-dimensionality Data Analysis of Pharmacological Systems Associated with Complex Diseases

“…Therefore, the acquisition and analogy of complex signaling data from multiple tissues simultaneously will likely create a more comprehensive view of systemic signaling paradigms. To this end, crowd-based platforms were recently developed to assist in network signaling prediction (Prill et al, 2011) and systems biology interpretation (Guryanova and Guryanova, 2017).…”

Integrated approaches in diagnostics and therapy of allergic diseases

“…Существующие сети KEGG [40], sbvIM-PROVER [41], Cytoscape [42] и др. трансформи-руют данные экспериментальных исследований в последовательность взаимосвязанных процес-сов, переход от системного представления о био-логических процессах к различным заболевани-ям [43], в том числе и аллергическим [44].…”