New year, new jinkō :) Model edit with graph, scatter plots, versioning and more!

With this new year come new key features in jinkō, with powerful model editing capabilities including a graph view, scatter plots, advanced versioning and more.

Model editing, with graphical  view

Model editing is now available for all jinkō users! It features an edition mode that can be used by modeling and non-modeling experts alike, alongside with a graphical view of your model for exploration. 

• Accelerate the edition and addition of parameters such as bioreactions, ODEs, events and categorical parameters with auto completion of formulae, unit checking, and automatic renaming of entities wherever they are used in the model.
• Understand, browse and search your model via an extensive and dynamic graph representation of the model focused on the component of interest and its neighbors. By controlling the depth of the graph you can easily analyze the links between the different components.
• If not using nova’s models library, you can upload your models in an SBML format in jinkō, they will be automatically transposed in a table format in jinkō, where they can be edited with augmented capabilities. Your uploaded model also becomes automatically available for exploration in a graphical view 

And also in modeling: 

• Custom tags: Easily categorize model components for collaborative edition of the models, or use of the model descriptors throughout jinkō, notably when building protocols for trials. For instance you can tag certain components as ProtocolSpecific so that Protocol Arms linked to this model are pre-set with those descriptor, you can also tag a subset of your model as "cell proliferation" and another one as "apoptosis" to then easily filter and display the submodels composing your computational model.

•  DDE: In addition to ODEs, jinkō now also supports Delayed Differential Equations (DDE) in the construction of models, both from import and from edition.

• Quick model solving: test your models by launching a trial in a few clicks, leverage jinkō trial simulations capabilities to quickly launch as many iterations as possible and refine your models

•  Phase portrait: run dual-variable co-analysis with our embedded phase portrait tool where you can compare different trajectories

Scatter plots

Use a scatter plot to visualize the relationships between different scalar results or different arms. The horizontal and vertical axis represent the chosen (descriptor - arm) couples, and each dot represents a virtual patient.

x vs x: 

• Base effect model (Relationship between the frequency (observation) or the probability (prediction) of a morbid event without any treatment (Rc) and the frequency or probability of the same event with a treatment (Rt)) on different arms
• Generalized / Stratified effect model on different arms (1 vs n)

x vs y: 

• Correlation between X and Y
• Stratified correlation between X and Y

Additional versioning capabilities

We keep rolling out new versioning capabilities in jinkō, now available for key trial components,  including models, protocols, output sets and (soon) the trial editor itself. Edit your item with full confidence and flexibility, knowing that you can browse and restore versions at any given time. 

And more! 

• Personal workspace with a demo NSCLC project + guided tours

All newly created accounts can now benefit from a Sandbox environment with unlimited access to our demo NSCLC model!

This environment features a comprehensive documentation on how to use the NSCLC model and sample material to get you started on your next simulation, such as:
- Virtual populations
- Protocols
- results visualizations

The sandbox environment also features guided step-by step tours to help new users master jinkō in no time.

Note that if you already have an account but would also like to have the sandbox account, we can create one for you on request, at support@jinko.ai.
 

• Improved capabilities for the SBML upload of a model

We keep expanding the rate of uploads successful from the first try on extensive test sets, including those from the SBML test suite (available on GitHub) and the Biomodels open Library, jinkō’s capability to integrate with this standard format from the industry have been consistently improving month over month, and is now reaching a significant milestone, all with the aim of integrating seamlessly with your existing models.

• Full support of categorical parameters

Create categorized arrays of parameters in your models to structure them, limit the context of use to what the model is aimed at (typically, a specific population or dose range) and ease the use of the parameters in other key items in jinkō, such as virtual populations and protocols.

• Trial monitoring

A new improved interface allows you to see how your trial is progressing and previsualise results for your outputs, while your trial is being run.

Keep in touch for additional updates, as we will be announcing new key releases very soon !