| Title: | Stress knowledge map : a knowledge graph resource for systems biology analysis of plant stress responses |
|---|
| Authors: | ID Bleker, Carissa (Author)
ID Ramšak, Živa (Author)
ID Bittner, Andras (Author)
ID Podpečan, Vid (Author)
ID Zagorščak, Maja (Author)
ID Wurzinger, Bernhard (Author)
ID Baebler, Špela (Author)
ID Petek, Marko (Author)
ID Križnik, Maja (Author)
ID Županič, Anže (Author)
ID Gruden, Kristina (Author) |
|---|
| Files: |  URL - Source URL, visit https://doi.org/10.1016/j.xplc.2024.100920
URL - Source URL, visit https://skm.nib.si
 PDF - Presentation file, download (1,35 MB)
MD5: E411194F1EC267F27BE12CD3DB83A435
|
|---|
| Language: | English |
|---|
| Typology: | 1.01 - Original Scientific Article |
|---|
| Organization: |  NIB - National Institute of Biology
|
|---|
| Abstract: | Stress Knowledge Map (SKM; https://skm.nib.si) is a publicly available resource containing two complementary knowledge graphs that describe the current knowledge of biochemical, signaling, and regulatory molecular interactions in plants: a highly curated model of plant stress signaling (PSS; 543 reactions) and a large comprehensive knowledge network (488 390 interactions). Both were constructed by domain experts through systematic curation of diverse literature and database resources. SKM provides a single entry point for investigations of plant stress response and related growth trade-offs, as well as interactive explorations of current knowledge. PSS is also formulated as a qualitative and quantitative model for systems biology and thus represents a starting point for a plant digital twin. Here, we describe the features of SKM and show, through two case studies, how it can be used for complex analyses, including systematic hypothesis generation and design of validation experiments, or to gain new insights into experimental observations in plant biology. |
|---|
| Keywords: | Stress knowledge map, knowledge graph, knowledge network, entry point, plant digital twin, plant stress responses, plant signaling, systems biology |
|---|
| Publication status: | Published |
|---|
| Publication version: | Version of Record |
|---|
| Publication date: | 10.06.2024 |
|---|
| Year of publishing: | 2024 |
|---|
| Number of pages: | str. 1-15 |
|---|
| Numbering: | iss. 6, [art. no.] ǂ100920 |
|---|
| PID: | 20.500.12556/DiRROS-19098  |
|---|
| UDC: | 577.2 |
|---|
| ISSN on article: | 2590-3462 |
|---|
| DOI: | 10.1016/j.xplc.2024.100920 |
|---|
| COBISS.SI-ID: | 198383363 |
|---|
| Note: | Soavtorji: Živa Ramšak, Andras Bittner, Vid Podpečan, Maja Zagorščak, Bernhard Wurzinger, Špela Baebler, Marko Petek, Maja Križnik, Annelotte van Dieren, Juliane Gruber, Leila Afjehi-Sadat, Wolfram Weckwerth, Anže Županič, Markus Teige, Ute C. Vothknecht and Kristina Gruden;
Nasl. z nasl. zaslona;
Opis vira z dne 11. 6. 2024;
|
|---|
| Publication date in DiRROS: | 11.06.2024 |
|---|
| Views: | 538 |
|---|
| Downloads: | 252 |
|---|
| Metadata: |    |
|---|
|
:
|
Copy citation |
|---|
| | | | Share: |  |
|---|
Hover the mouse pointer over a document title to show the abstract or click
on the title to get all document metadata. |
