The representation of biological processes as comprehensive signalling network maps has three major goals:

(i) To generate a resource containing a formalized summary of biological findings from man research groups

(ii) To provide a platform for sharing information and discussing biological mechanisms and

(iii) To create an analytical tool useful for high-throughput data integration and analysis.

It can be helpful to systematically represent and formalize the molecular information distributed in thousands of scientific publications. An additional advantage of representing biological processes in a graphical form is to capture the multiple cross-talks and interactions occurring between different cell processes.

Analysis and visualization of omics data in the context of signalling network maps can help to detect patterns in the data projected onto the molecular mechanisms there represented. For instance, identification of deregulated mechanisms and key players in human diseases has a direct clinical application. Moreover, correlating the status of those deregulated mechanisms with patient survival helps for patient stratification according to their network-based signatures. Due to the complexity of mechanisms simultaneously involved in diseases, targeting combinations of molecular players is now the trend in treatment of complex diseases. The computational approaches using signalling maps allow testing multiple combinations in silico, considering large comprehensive signalling networks and omics data. In addition, signalling networks can serve for modelling and prediction of cell fate decisions and suggestion of non-intuitive combinations of gene perturbations to explain phenotypes in health and disease.

To achieve these goals, the construction of a signalling map should become an accessible procedure that can be completed in a reasonable time. There are several solutions for biological knowledge formalization briefly described in this manuscript. We contribute to this global aim and formulate the main principles and steps of the established workflow for manual map construction. In addition, we suggest the biological network map navigation facilitated by Google Maps technology and provide examples of data analysis and visualization in this context.

Diagram types for molecular processes representation

Generally speaking, there are four main approaches (or diagram types) for representing molecular processes, each of them characterized by a certain depth of description:

interaction diagram, which shows simple binary relations between molecular entities;(ii) activity-flow, known as regulatory network or influence diagrams, representing the flow of information or influences of one entity on another; (iii) entity relationship diagram, depicting relations in which a given entity participates; and (iv) process description (PD) diagram, known in chemical kinetics as bi-partite reaction network graphs.

Pathways and network maps approached for molecular processes representation

Using the aforementioned approaches of molecular processes representation, several pathway databases have emerged. They serve as biological knowledge information resource and as computational analytical tools for systems-based interpretation of data. A significant number of pathway databases have been also developed in the private domain, but the majority of pathway collections are free and open source.

Common standards for molecular processes representation

With the aim of creating a collection of exchangeable comprehensive signalling maps, common rules for drawing maps and standard graphical syntax should be developed and consistently applied. The current suggested solution in the field is the Systems Biology Graphical Notation (SBGN) syntax. This syntax is compatible with various pathway drawing and analytical tools, allowing representing not only biochemical processes but also cell compartments and phenotypes. Furthermore, to increase cross-compatibility between pathway resources and analytical tools, several common formats for exchanging information on molecular interactions, such as BioPAX, SBML, PSI-MI and so on, have been suggested.

A workflow for construction of comprehensive signalling network maps

In this manuscript, we describe a set of good practices for building comprehensive signalling network maps. We provide the methodology that allows overcoming challenges associated with construction, navigation and exploration of large molecular interaction maps. We suggest an approach that is neither unique nor universal but provides verified practical solutions to comprehensive map construction and manipulation that successfully served to generate the ACSN resource and also applied in other studies.

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