Accepted lightning talks at HARMONY 2019

This is current as of 2019-03-20. Note: the following list is not in presentation order (or really in any order at all).

BioSCRAPE: a Fast Object Oriented Python/Cython CRN Simulator

William Poole (Caltech)
Anandh Swaminathan (Formerly Caltech)

BioSCRAPE (Bio-circuit Stochastic Single-cell Reaction Analysis and Parameter Estimation): a Python package for fast and flexible modeling and simulation highly customizable chemical reaction networks. Specifically, bioscrape supports deterministic and stochastic simulations which can incorporate delay, cell growth, and cell-division. Models can beconstructed via systems biology markup language (SBML), a simple internal XMLlanguage, or specified programatically via a python API. Simulation run times obtained with the package are comparable to those obtained using C code - this is particularly advantageous for computationally expensive applications such as Bayesian inference or simulation of cell lineages.
Web page with more information: https://github.com/ananswam/bioscrape

BioCRNpyler: A pythonic CRN Compiler for synthetic and systems biologists

William Poole (Caltech
Ayush Pandey (Caltech)
Zoltan Tusa (Imperial College London)
Richard Murray (Caltech)

BioCRNpyler is a highly flexible framework for rapidly generating large chemical reaction network models for synthetic and systems biology from simple user specifications. For example, given a set of genes with promoters and ribosome binding sites, it generates full transcriptional and translational networks with the relevant machinery (eg polymerases, endonucleases, ribosomes, etc.), genetic regulation, and more. This framework uses an reaction schema approach to allow for models with diverse levels of detail to be very easily generated in a programatic way. Generated models can be simulated with BioSCRAPE or exported as SBML.
Web page with more information: https://github.com/WilliamIX/BioCRNPyler

InSilico: an eclipse-based framework for plugin-development and standards interoperability

Andreas Dräger
Roman Schulte
Matthias König

InSilico is a project based on Eclipse and JavaFX for the integration and management of various apps to facilitate the processing of scientific models and data as well as the development of end-user software. This talk presents the features of the framework and explains how to get involved.
Web page with more information: https://github.com/draeger-lab/insilico/

Krayon for SBGN: a new graphical process diagram editor for SBGN-ML

Thomas M. Hamm
Roland Wiese
Andreas Dräger

Krayon is a yFiles-based editor for SBGN diagrams that is written in Kotlin. In this talk we will give a brief overview of the program and its various features, such as loading, saving, drawing, and manipulating process diagrams that can be printed and exported to PNG, GIF, JPG, SVG, PDF, and EPS. Krayons allows users to apply predefined diagram styles easily and has a customizable user interface. We are currently working towards a full integration of Krayons into the InSilico framework for interoperability with SBML models.
Web page with more information: https://github.com/wiese42/krayon4sbgn

Recent Updates in the Synthetic Biology Open Language

Chris Myers (University of Utah)

In this talk, we will present recent updates to the Synthetic Biology Open Language (SBOL). In particular, there have been several proposals accepted for SBOL Visual 2.1 and SBOL data 2.3. In addition, this presentation will present the current state of SBOL related libraries and other SBOL software.
Web page with more information: http://sbolstandard.org

Bringing SBML Layout and Render to Python

Natalie Hawkins (UW)
Ion Moraru (UConn)
Herbert M Sauro (UW)

In this lightning talk we will discuss the work we have been doing to make it easier to access the SBML layout and render extensions from Python. We will show how it is possible to use Python's Matplotlib to display networks encoded using SBML and present an easier to use API for SBML Layout and Render manipulation.
Web page with more information: https://github.com/sys-bio/libsbml-draw

SBMLLint - A Tool for Linting SBML Models to Detect Errors in Mass Balance

Joseph L. Hellerstein (eScience Institute, University of Washington)
Woosub Shin (eScience Institute, University of Washington)

A linter is a software tool that detects errors by a static analysis of codes, such as pylint that detects if a variable is referenced before it is assigned a value. It is common in kinetics models, constraint models, and other reaction-based models to have mass balance errors whereby one or more reactions incorrectly includes (or excludes) a chemical species in the reactants or products so that the total mass of the reactants does not equal the total mass of the products. We have developed SBMLLint, a tool for linting SBML models to detect and identify reactions with errors in mass balance. An analysis of 729 curated BioModels revealed that over 120 models have at least one reaction with a mass balance error. We give examples of the errors detected. An initial release of SBMLLint is planned for May.
Web page with more information: https://github.com/ModelEngineering/SBMLLint

MulticellML - Standardising the exchange of multicellular models in systems medicine

Martin Golebiewski (HITS, Heidelberg, Germany)
Lutz Brusch (Technical University Dresden, Germany)
Jörn Starruß (Technical University Dresden, Germany)
Walter de Back (Technical University Dresden, Germany)
Haralampos Hatzikirou (Helmholtz Centre for Infection Research, Braunschweig, Germany)
Wolfgang Müller (HITS, Heidelberg, Germany)

New insights into multicellular processes in tissues and organs, like tissue regeneration, can be gained using spatially resolved modelling and simulation. Correspondingly, many international Systems Medicine projects develop spatially resolved multicellular models and new simulation software. However, the exchange, reproducibility and archiving of spatially resolved multicellular models among different projects with different software tools is currently hampered by the lack of an appropriate and fully declarative model definition language for this model class. The project MulticellML aims at developing an infrastructure for the exchange of spatially resolved multicellular models within and among projects. The project plans to combine the established data management framework FAIRDOMhub/SEEK with a fully declarative model description language for spatially resolved multicellular models.
Web page with more information: https://www.sys-med.de/en/networking/spalte-2/networking-fonds/multicellml/

EU-STANDS4PM - A European standardization framework for data integration and data-driven in silico models for personalized medicine

Martin Golebiewski (HITS, Heidelberg, Germany)

EU-STANDS4PM will establish a pan-European expert forum with two main objectives: (i) to assess and evaluate national standardization strategies for interoperable health data integration (such as omics-, disease-focused-, clinical-/treatment- or healthcare- and socioeconomic-/lifestyle-data) as well as data-driven in silico modelling approaches and (ii) to harmonize and develop universal (cross-border) standards as well as recommendations for in silico methodologies applied in personalized medicine approaches. It has the overarching aim to bundle transnational standardization guidelines for in silico methodologies in transnational and clinical research to: - Harmonize health and disease data integration strategies to further strengthen data-driven in silico modelling approaches for personalized medicine in Europe (and beyond) - Facilitate a sustained use of Life Science data in clinical and health research - Advise regulatory authorities on a broad adaptation of harmonized health data and standards in research, and industry - Enable FAIR principles (Findable, Accessible, Interoperable and Reproducible) as well as legal and ethical requirements for the above tasks By harmonizing and standardizing data-driven approaches across multiple disciplines and stakeholders EU-STANDS4PM will ease an accelerated use of health data in clinical research and practice thus unfolding the potential of predictive in silico models in personalized medicine.

libsbmljs: A Web-capable SBML JavaScript Library

Herbert Sauro (Univ. Washington, Seattle)
Kyle Medley (Univ. Washington, Seattle)
Kiri Choi (Univ. Washington, Seattle)

The SBML standard is used in many online repositories such as BioModels, BiGG Models, and JWS Online. However, there is currently no JavaScript library for SBML which can run in a web browser. This talk introduces libsbmljs, the first fully-featured JavaScript SBML library that works in the browser. libsbmljs supports all SBML Level 3 packages, and is extremely useful for web apps such as Escher which read and write the SBML standard. We hope this library will enable online SBML editors and simulators, especially for model repositories.

NUPACK Software Engineer

Grant Roy (Caltech)

Basic overview of NUPACK, a software suite for the analysis and design of nucleic acid structures, devices, and systems.

Latest developments in Tellurium and libRoadRunner

Herbert Sauro
Lucian Smith
Andrew Hu
Kiri Choi

In this talk we will give a brief update on the Python platform Tellurium and the latest developments in the supporting libraries Antimony and libRoadrunner.

Reusable library for annotating SBML and CellML models stored in COMBINE Archives

Herbert Sauro
Kyle Medley
John Gennari

In this presentation, we will describe a new annotation library developed in C/C++ that can be hosted by other applications to support annotation of SBML and CellML models stored in Combine archives. The library is based on earlier work done with Semgen. The library will be demonstrated using its Python API. We hope this library will help encourage more consistent annotation of models. All source code is available on GitHub under the MIT open source license. Currently, C++ and Python APIs are available with a C API and other bindings to be added later.

StochSS: A Next-Generation Toolkit for Simulation-Driven Biological Discovery

Linda Petzold (University of California Santa Barbara)
Brian Drawert (University of North Carolina Asheville)
Andreas Hellander (Uppsala University, Sweden)
Michael Hucka (Caltech)

In this talk, we will summarize StochSS, a novel and easy to use Software-as-a-Service offering for quantitative modeling of biochemical networks capable of seamless deployment in public or private cloud environments, as well as your laptop. StochSS integrates advanced algorithms for modeling biochemical systems on multiple levels, ranging from simple deterministic ordinary differential equations (ODEs), through discrete stochastic models simulated via the Stochastic Simulation Algorithm, all the way to detailed spatial stochastic models capturing stochasticity as well as molecular movement and realistic cellular geometries. In addition to its core simulation capabilities, Next-Gen StochSS will have two new features: the Model Development Toolkit (MDT) for constructing models from time-series data, and the Model Exploration Toolkit (MET) for exploring the parameter space to discover the qualitatively distinct behaviors the model can yield, within the space of uncertain parameters.