Systems Biology
Systems Biology Tools developed by IGB are highlighted by research and collaborations in the areas of:
Circadian Rhythms
| Circadiomics | The main functionality of CircadiOmics is the search, comparison and visualization of oscillation trends.
The omic datasets available on CircadiOmics are compiled from project collaborations, automated discovery and manual curation. Over 6400 individual time points spanning 227 separate circadian experiments corresponding to over 74 million measurements sampled over 24 h cycles are available for search and visualization. |
| BIO_CYCLE | BIO_CYCLE, a deep learning-based system to robustly estimate which signals are periodic in high-throughput circadian experiments, producing estimates of amplitudes, periods, phases, as well as several statistical significance measures. |
Parameter Inference for Stochastic Gradient Decent
Stochastic effects can be important for the behavior of processes involving small population numbers, so the study of stochastic models has become an important topic in the burgeoning field of computational systems biology. However analysis techniques for stochastic models have tended to lag behind their deterministic cousins due to the heavier computational demands of the statistical approaches for fitting the models to experimental data. There is a continuing need for more effective and efficient algorithms.
Transcription/RNA Splicing, Coupling, and Modeling
| Tool | Description |
| Cellerator Information: | Equation generator and simulator for biological modeling |
| RNA Splicing Modeling: | Enzyme mechanism language for the mathematical modeling of transcription/RNA splicing coupling |
| Computable Plant Information: | Quantitative and cellular description of plant development |
| Metabolic Modeling | Several tools for modeling metabolic pathways and bioenergetics |