GSoC/GCI Archive
Google Summer of Code 2015

University of Nebraska - Helikar Lab

License: Academic Free License 3.0 (AFL 3.0)

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Our group works at the interface of computer science, biology, and mathematics by applying computational approach to the seas of data in biomedical 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. Our recent web-based technology, the 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. The 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 mal-function can have on the rest of the cell.

Our group is part of the Department of Biochemistry at the University of Nebraska-Lincoln, and consists of computer scientists, biologists, bioinformaticians, as well as mathematicians, creating an unique environment of diverse skills, yet integrated by a single interest point.


  • Interactive Platform for Statistical Computing A proposal for designing an interactive web front-end to allow the end user, ideally, somebody unfamiliar with programming in R, to perform powerful analyses and examine and tweak data in a user-friendly, simplified manner, using an R back-end.
  • Mobile¬≠-based Blood¬≠-Sample Image Analysis Project aims to develop android application for a screening test for the detection of cancer bio-marker(s) from a small drop of blood. Many softwares exist for Blood sample image analysis, but most of them contain a trade-off between portability and accuracy. Using the state of art Image processing techniques and camera-equipped mobile devices with sufficient processing capacity, developing a reliable application that performs screening test for cancer biomarker detection is feasible.
  • Visualisation of Large Scale Biological Networks with Interactivity 1.Implementation of Different Layouts. --Spectral Layout --Force Layout optimized for biological networks --Hierarchical layout 2. Interactivity: --Add/Remove Node/edge --Selection/styles --panel to do all the above functions