GoSyn Doucument: Tutorial - 2011


All the data described are additionally available as an easy to use synthetic biology workbench in the internet under the following link:

The compilation includes recent references to synthetic biology efforts, the new workbench for cellular processes and its related topology.

The aim of the GoSyn homepage is to transfer biological processes and functions of different organisms into technical processes. These processes are subsequently divided into smaller subunits – so-called modules – in order to dissect and simplify the process. The simplification is a prerequisite for the generation and manipulation of new biological processes.

A statistical survey displays the distribution of biological modules

Moreover a description of the modules and the assignment between technical terms and biological modules is provided.

The user should select the organism (man, mouse, E.coli), 7 different main modules and 23 sub modules. For chosen organism and module, a separate page is provided with a description of the module, a list of MESH-terms and a table with the corresponding go-terms, proteins and cog families. Further information and sequences are available as database cross-links.

For an easier access, two different search scenarios are applicable, either based on keyword terms or on process search. The results are visualized by text-highlighting functions, which are supported by graphical statistics and interaction networks to other partner proteins.

  1. Keyword-search: is an AMIGO like search. The keyword search is resulting in a list of all modules which contain GO-terms with the search-keyword highlighted in red. The keyword search is trivial but useful for GO terms searches.

  2. Process-search: is a search for biological and technical processes. Based on the buzzword entered, a regular keyword search is performed in the background. For the identified GO-terms all proteins connected to these processes are selected. The modules of the protein’s functions are presented as results. The result is provided as text information and as graphical pie charts. One pie chart provides an overview over all modules while individual pie charts are additionally shown per module.

Keyword search example:

Entered keyword: glycolysis

Selected organism: Homo sapiens

Result: Glycolysis in Homo sapiens can be found in three different modules: Activation, Pathway and Regulation.

Process search example:

Investigated process: Glycolysis

Selected organism: Homo sapiens

Result: The first pie chart shows that the process is dominantly a strongly regulated pathway.

Additional pie charts describe further information: the process is mainly positively regulated and is linear within an active cell.

A connection with the interaction database IntAct provides the opportunity to identify interactions and connections to other biological processes including graphical network visualization. Direct translation of processes and modules in biological organisms and protein interaction networks may be retrieved including gene ontology searches. This allows easy construction of own novel networks containing desired technical or biological modules. The GO synthetic software can be used as an intuitive and creative tool for process engineering as well as for the design of new experiments.

As a result a list is provided which contains all modules that have been identified within the process. The list additionally displays the related processes and the connection between these processes. Proteins within the process can be added.

The terminology can be switched between technical and biological modules.

Visualization shows the interaction between the proteins in the process based on the IntAct database. Activating proteins are highlighted in orange, while inhibitory proteins are highlighted in blue.

The visualized result and protein assembly can be readily exported into the open-source Cytoscape platform (Cline et al., 2007 for the dynamic visualization of molecular interaction networks. It is also possible to modify the network further and assign additional data (gene expression metrics; any other desired data sets) and/or detailed functionalities to each network element.

Together with biological expert analysis (such as literature search and interactom search) even more extended examples can be explored with the two-level classification (see supplement information and results).

GoSynthetic initiated by Beate Krueger, Dr. Chunguang Liang, Dr. Qian Zhang, supervised by Prof. Dr. Thomas Dandekar, Copyright reserved 2008-2013.