News
Talk at Biocuration Conference
04-04-2023
SABIO-RK will be presented in a lightning talk at the 16th Annual International Biocuration Conference on April 24-26, 2023 in Padua (Italy).
The presentation will highlight the new visualization of SABIO-RK data published recently:
Dorotea Dudaš, Ulrike Wittig, Maja Rey, Andreas Weidemann, Wolfgang Müller
Improved insights into the SABIO-RK database via visualization
Database
Volume 2023 (2023) baad011
https://doi.org/10.1093/database/baad011
SABIO-RK paper in "Database"
04-03-2023
The new visualization of SABIO-RK data is now published in the Database Journal.
To get a better overview about the multidimensional and complex data in SABIO-RK we developed a variety of visualization concepts in the SABIO-RK user interface. We use a heat map, parallel coordinates and scatter plots to allow the interactive visual exploration of general entry-based information of biochemical reactions and specific kinetic parameter values.
Dorotea Dudaš, Ulrike Wittig, Maja Rey, Andreas Weidemann, Wolfgang Müller
Improved insights into the SABIO-RK database via visualization
Database
Volume 2023 (2023) baad011
https://doi.org/10.1093/database/baad011
EnzymeML in Nature Methods
02-15-2023
A Paper about EnzymeML serving as a seamless communication channel between experimental, modeling, and publication platforms published in Nature Methods. SABIO-RK integrates kinetic data from the EnzymeML data flow.
Lauterbach S, Dienhart H, Range J, Malzacher S, Spöring JD, Rother D, Pinto MF, Martins P, Lagerman CE, Bommarius AS, Høst AV, Woodley JM, Ngubane S, Kudanga T, Bergmann FT, Rohwer JM, Iglezakis D, Weidemann A, Wittig U, Kettner C, Swainston N, Schnell S, Pleiss J.
EnzymeML: seamless data flow and modeling of enzymatic data.
Nat Methods. 2023 Feb 9.
https://www.nature.com/articles/s41592-022-01763-1
More details in the HITS News
SABIO-RK understands EnzymeML
10-06-2022
In the last years we collaborated with Jürgen Pleiss and others on the development of EnzymeML - a markup language that represents a data exchange format for biocatalysis and enzymology.
As a case study the extraction and storage of data described by EnzymeML documents was implemented in the SABIO-RK workbench.
The full paper can be found here The FEBS Journal 289(2022) 5864–5874
Poster at COMBINE and ICSB
09-29-2022
The new visualization of SABIO-RK data including kinetic parameters is presented by Dorotea Dudaš at the COMBINE 2022 and at the International Conference on Systems Biology (ICSB) in Berlin in October 2022.
Poster title: Deep insight into SABIO-RK data via visualization
Authors: Dorotea Dudaš, Maja Rey, Ulrike Wittig, Andreas Weidemann, Wolfgang Müller
New Visualization in SABIO-RK
09-29-2022
In order to facilitate interactive search and data refinement through the SABIO-RK
data, a new visualization module is developed. Its goal is to improve the
understanding of the database content and detect possible discrepancies between
kinetic parameters from different publication sources. It is meant to support both
modellers and experimentalists to extract the highest possible amount of information
from accumulated and orderly presented data. Clustering and grouping of the data
(e.g. kinetic parameters, EC numbers, environmental conditions) is implemented.
Reactions, proteins/enzymes, organisms, tissues and experimental conditions (pH
and temperature) are included within three different visualization concepts
representing a heat map overview, parallel coordinates and a scatter plot matrix with
histograms. Since each database entry can contain several kinetic parameters (with
its types, values, units and associated species) they are shown in two separate
visualizations. This improves the possibilities of exploring the kinetic data and its
connections to the rest of the data in SABIO-RK. Data can be visually adjusted by
determining what exactly is shown within the graphs, by reordering the data and by
selecting different color schemes for the visualizations using the user interface.
The new visualizations enable navigating through the database without the need to
know much about available keywords in the database or about manually composing
search queries.
