Tool development in bioinformatics, computational biology, data visualization

Our team works at the interface of computer science, biology, and mathematics by applying computational approaches to the seas of data in life sciences research. One of the main interests of our group is the development of technologies to make large-scale computational approaches accessible and more collaborative to a wider scientific audience. For example, our web-based technology, Cell Collective, enables scientists from across the globe to construct and simulate large-scale computational models of biological systems in a highly collaborative fashion. This software enables biomedical researchers to study the dynamics of biological systems (e.g., cells) under both healthy and diseased conditions. Cell Collective provides a unique environment for real-time, interactive simulations to enable users to analyze and visualize the multitude of effects a disease-related malfunction can have on the rest of the cell.

Our technologies have broad impact in education: Traditional didactic and textbook-based learning formats utilized in many life sciences courses create an environment that limits student ability to develop highly needed technical skills and fully conceptualize the complex and dynamic nature of biology and diseases. To address these challenges, our software technologies enable students ranging from high schools to undergraduate and graduate levels to learn about biology and diseases using by building, simulating, breaking, and re-analyzing computational models of these biological systems.

Other technologies developed by our organization include cost-effective mobile disease monitoring devices, interactive on-line tissue sample analysis, an interactive statistical analysis platform for teaching life sciences students about data analysis, etc. Our group consists of computer scientists, biochemists, biologists, bioinformaticians, as well as mathematicians, creating an unique environment of diverse skills, integrated by a single interest point.

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  • javascript
  • react
  • postgresql
  • webgl


  • Science and Medicine
  • web application
  • bioinformatics
  • computational biology
  • data science
  • network biology
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Computational Biology @ University of Nebraska-Lincoln 2019 Projects

  • Caner Akda┼č
    Advanced Node, Edge, Arrow Plugin Library
    Advanced Node, Edge, Arrow Plugin Library This plugin draws the desired types of nodes and arrows on a non-visible canvas. These dynamically drawn...
  • Himanshu Jotwani
    ccNetViz Project : Advanced Custom Label And Text Formatting
    The Purpose of this project is to add advanced label formatting features to the ccNetviz library for graph Visualizations without affecting the...
  • Xiaodong Zhao
    Edge Animations for Large-Scale Network Graphs
    With ccNetViz, this large graph render library using WebGL, I'll add edge animations on it. Including color animations, speed control and other fancy...
  • Aman Dave
    Web Pipeline for Flux Balance Analysis
    The project is based upon Flux Balance Analysis, which is a model used for simulating metabolism. It is used in genome-scale reconstructions of...
  • Mohamed Shadab
    Web Pipeline For Kinetic (ODE-Based) Models
    Ordinary differential equations are widely used for modelling biological networks and processes of kinetics. The idea of the project is to create a ...