Data Visualization
PathSys data visualization is done through the Client Side Application, ,
which implements all business logic and a significant part of the user interface.
Sound Data Model together with strong Ontology capturing a big
variety of biological data types is crucial for modeling capabilities of the
system. But networks of molecular interactions derived from current biological
data are incomplete and complicated. Complete network is clearly beyond human
perception. Therefore different levels of abstractions are necessary
to make effective analysis of cellular processes and dealing with complexity
better.
One of such abstractions presented in PathSys&BiologicalNetworks is
Meta-Node (or Graph Node).
Representing a cellular pathway as a single process or grouping related processes
under a certain cellular mechanism enhance the comprehensibility of the networks
of events. Grouping examples presented in PathSys&BiologicalNetworks are:
domain structure of a protein, complex of multidomain proteins, chromosomal
regions (promoters, binding sites, etc.) bound to a gene or group of genes,
protein with its phosphorylation sites, gene transcription and mRNA translation
or degradation mechanisms, whole metabolic pathway etc. Remember that grouping
could be done over any data type object from Node Types hierarchy.
Since the data on cellular processes is not complete, different levels of
information may be available for certain events. In case where it is not identified
which state among a set of states constitutes the substrate, product or effector of
a process, or where target process of an effector is obscure, we may need
to abstract these states or/and processes in a single state/process to represent
the available information despite its incomplete nature (see Figure1 below).
Figure1. Abstraction helps better handling of complex information. For
instance, part of a pathway may be collapsed to simplify relatively more
complex graph (a->c, b->d). Two types of abstractions for representing
information of incomplete nature: State and process abstraction. In addition
(b, d) there are regular abstractions, "protein degradation", "gene
expression", etc.
