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README.md

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-# Welcome to CSB
+# CSB GitHub Org page
 
-This is the GitHub organization for the **Computational Systems Biology** department of the RPTU Kaiserslautern.
-
-You can read more about the following topics on our [website](https://csbiology.github.io/):
-- [research](https://csbiology.github.io/#research)
-- [teaching (university courses and projects)](https://csbiology.github.io/#teaching)
-- [publications](https://csbiology.github.io/#publication)
-- [team](https://csbiology.github.io/#team) 
-
-# Our Research
-
-The capability of biological systems to respond to environmental changes is realized by a complex dynamic adjustment of the interplay between genes, proteins and metabolites. 
-For a deeper understanding at the systems level, we need to study the structure and dynamics of cellular and organismal functions rather than the characteristics of isolated parts of a cell or an organism.
-
-## Research data management (RDM)
-
-We are committed to the success of FAIR (Findable, Accessible, Interoperable, and Reusable) and open research data.
-Research data possess immense value, which, when combined with tomorrow's technologies such as machine and deep learning, can unlock answers to questions we cannot even conceive today.
-Therefore, the flexible contextualization of research data with machine-actionable metadata is essential to advance modern science.
-
-We draw inspiration from the open-source software community's success, developing approaches that enable the biological community to collaboratively build a community-wide FAIR research data resource.
-Our research group participates in the National Research Data Infrastructure (NFDI) initiative with the [DataPLANT project](https://github.com/nfdi4plants), which empowers plant researchers to engage in a thriving RDM ecosystem without barriers.
-
-## Biological Data Science
-
-Modern technologies now allow researchers to simultaneously study biological organisms and processes across various molecular layers and in diverse biological contexts.
-To leverage this wealth of data, we are developing advanced methods for both supervised and unsupervised analysis of multi-modal omics data using cutting-edge machine learning and statistical modeling techniques.
-As part of fslabs.org, we contribute to the open-source data analysis library environment, ensuring that our innovations are accessible to the broader research community.
-Our methods enable comprehensive, data-driven integration and analysis of data derived from multiple omics technologies and varied biological scenarios, thereby enhancing our understanding of complex biological systems.
-
-## Prediction of acclimation modulators and integrators based on ‘omics data
-
-Acclimation responses involve complex interactions among genes, proteins, and metabolites, resulting in both general and specific elements.
-Previously, we focused on extracting response-specific structural models from complex 'omics data using functional constraint aggregation and network topology inference.
+- `/profile/README.md` contains the content displayed at the org homepage
+- Discussions Tab is used for overall organization discussions (if needed)